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senior lead software engineer

Information Technology Senior Management Forum

<div><div>Posted Date
6/29/2026
</div><div>Description
<div>Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)
Overview:
At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Team Description:
The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. 
In this role, you will:<ul><li>
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.</li><li>
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.</li><li>
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.</li><li>
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.</li><li>
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.</li></ul>
The Ideal Candidate:<ul><li>
You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.</li><li>
Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.</li><li>
You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.</li><li>
You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.</li><li>
You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.</li></ul>
Basic Qualifications:<ul><li>
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies</li><li>
At least 6 years of experience programming with Python, Go, Scala, or Java</li></ul>
Preferred Qualifications:<ul><li>
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)</li><li>
Experience designing, developing, integrating, delivering, and supporting complex AI systems</li><li>
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders</li><li>
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang</li><li>
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost</li><li>
Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production</li><li>
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer 

Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)
Overview:
At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Team Description:
The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. 
In this role, you will:<ul><li>
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.</li><li>
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.</li><li>
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.</li><li>
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.</li><li>
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.</li></ul>
The Ideal Candidate:<ul><li>
You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.</li><li>
Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.</li><li>
You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.</li><li>
You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.</li><li>
You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.</li></ul>
Basic Qualifications:<ul><li>
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies</li><li>
At least 6 years of experience programming with Python, Go, Scala, or Java</li></ul>
Preferred Qualifications:<ul><li>
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)</li><li>
Experience designing, developing, integrating, delivering, and supporting complex AI systems</li><li>
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders</li><li>
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang</li><li>
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost</li><li>
Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production</li><li>
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer 

Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>
</div><div>Salary
229,900.00 - 262,400.00 Annual
</div><div></div><div><div>Type<div>
Full-time</div></div></div></div>

Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)

Decagon

<div>About Decagon
Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.
Our technology enables industry-defining enterprises like Avis Budget Group, Block&rsquo;s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.
We&rsquo;re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We&rsquo;re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.
We&rsquo;re an in-office company, driven by a shared commitment to excellence and velocity. Our values &mdash; Just Get It Done, Invent What Customers Want, Winner&rsquo;s Mindset, and The Polymath Principle &mdash; shape how we work and grow as a team.<h2 class="jobSectionHeader">
About the Team</h2>
The Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.<h2 class="jobSectionHeader">
About the Role</h2>
We&rsquo;re looking for a Senior Software Engineer to help build and evolve our internal developer platform&mdash;everything from CI/CD and release automation to observability standards, platform tooling, and developer workflows that remove friction.
This role is for someone who loves making other engineers faster: reducing build times, eliminating flaky tests, creating paved roads for service creation/deployment, and raising the bar on operability by default. Roles like this often combine &ldquo;builder&rdquo; energy with strong empathy for how engineers actually work.<h2 class="jobSectionHeader">
What you'll do</h2><ul><li>
Developer productivity &amp; platform tooling<ul><li>
Identify workflow bottlenecks (build/test/release/local dev) and build tools that measurably reduce toil.</li><li>
Create and maintain &ldquo;golden paths&rdquo; like service templates, CLIs, libraries, and automation that teams rely on.</li></ul></li><li>
CI/CD &amp; release engineering<ul><li>
Design reusable CI pipelines and deployment workflows that are fast, safe, and easy to adopt across teams.</li><li>
Improve reliability of builds and tests (flake reduction, hermeticity, caching) and drive down cycle time.</li><li>
Support progressive delivery patterns (canary / blue-green) and safe rollback mechanisms.</li></ul></li><li>
Observability &amp; operational excellence<ul><li>
Establish shared observability primitives (metrics/logs/traces), standards, and libraries so services are production-ready by default.</li><li>
Partner with product engineers to improve operability: SLOs, alerting hygiene, dashboards, incident learnings.</li></ul></li><li>
Infrastructure foundations<ul><li>
Build and improve core platform capabilities that make it easy to run and scale services.</li></ul></li><li>
Ownership &amp; reliability<ul><li>
Own the systems you build end-to-end and help keep them healthy in production, improving reliability over time.</li></ul></li></ul><h2 class="jobSectionHeader">
Your background looks something like this</h2><ul><li>
4+ years building production software, with meaningful experience in platform / devtools / infrastructure (or adjacent SRE/release engineering).</li><li>
Strong coding ability in at least one systems/productivity language (e.g., Python, TypeScript/JS), and comfort building developer-facing tooling (CLIs, libraries, automation).</li><li>
Hands-on experience with CI/CD systems and designing pipelines that are scalable and reusable across many repos/services.</li><li>
Practical experience with observability in production systems (instrumentation, alerting, dashboards, incident response).</li><li>
Comfort with containers and modern cloud infrastructure (e.g., Docker/Kubernetes and related tooling).</li><li>
A track record of improving developer experience through measurable outcomes (faster builds, fewer flakes, safer deploys, fewer incidents).</li><li>
Strong cross-team collaboration and communication&mdash;especially writing clear docs and driving adoption.</li></ul><h2 class="jobSectionHeader">
Even better if you have</h2><ul><li>
Experience with monorepos and build systems and/or large-scale CI performance work.</li><li>
Experience building internal platforms: service templates, paved-road deployment, self-serve environments, developer portals.</li><li>
Infrastructure-as-code experience (e.g., Terraform) and a security-minded approach to supply chain (provenance, secrets, least privilege).</li><li>
Experience applying AI-assisted tooling to make engineers dramatically more effective.</li></ul><h2 class="jobSectionHeader">
Compensation</h2>
$200K &ndash; $400K + Offers Equity 
 
This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact.
 
 
In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States.
Benefits
We proudly offer the following benefits for our full-time employees:<ul><li>
Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)</li><li>
Medical, Dental, and Vision benefits for you and your family</li><li>
Life Insurance and Disability Benefits</li><li>
Retirement Plan (e.g., 401K, pension)</li><li>
Parental Leave</li><li>
Fertility and family building benefits through Carrot</li><li>
Daily lunches and snacks in the office to keep you at your best</li></ul>
These benefits are described in more detail in Decagon&rsquo;s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Compensation Range: $200K - $400K</div>

Senior Software Engineer, Platform Engineering

Google

<div>Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience. 
</li>
<li>8 years of experience with software development. 
</li>
<li>7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).</li>
<li>5 years of experience in a technical leadership role.</li>
<li>5 years of experience in a people management or team leadership role.</li>
<li>2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal etc.) or with GenAI-related concepts.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master&rsquo;s degree or PhD in Engineering, Computer Science, or a related technical field. 
</li>
<li>5 years of experience working in a complex, matrixed organization. 
</li>
<li>Experience in building and deploying Agentic AI systems.</li>
<li>Experience in security domains.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way. 
 
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. 

Our team is at the forefront of revolutionizing Google Security Operations (SecOps) through the power of artificial intelligence. We are developing a Security Agentic Platform to enable the development of first-party and third-party security agents to deliver a proactive, intelligent, and automated Agentic Security Operations Center (SoC).
 
 
In this role, you will lead a team of talented engineers in building the next generation of Security Agentic AI platforms and systems that will protect major organizations worldwide.
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
 
 
US: $262000 - $365000 (USD) + 25% bonus target + equity + benefits 
 
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Guide, mentor, and grow a team of engineers focused on developing and deploying agentic AI for security that will power the Google Unified Security products.</li>
<li>Manage the technical goal and strategy for the Security Agentic AI, ensuring alignment with the broader security teams.</li>
<li>Collaborate with cross-functional engineering teams along with product management, data science, and security engineering to define product requirements and roadmaps, and deliver features.</li>
<li>Oversee the end-to-end development lifecycle, from ideation and design to implementation, testing, and deployment of AI-driven agentic security solutions.</li>
<li>Foster a culture of innovation and continuous improvement, staying abreast of the latest advancements in AI, machine learning, and cybersecurity.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Software Engineering Manager, Agentic Platform, Cloud Security

Alembic Pharmaceuticals Ltd

<div>About Us
Alembic is the pioneering Causal AI platform. We help the world's largest enterprises move past correlation to prove what actually drives business outcomes &mdash; the question marketing and growth teams have never been able to answer with confidence. Fortune 100 companies including Nvidia, Delta Air Lines, and Mars use Alembic to make multimillion-dollar decisions on trusted, causal evidence.
We're backed by a $145M Series B from WndrCo (founded by Jeffrey Katzenberg), Jensen Huang, Joe Montana, Prysm Capital, and Accenture. Our models run on our own NVIDIA DGX SuperPOD built on Grace Blackwell infrastructure &mdash; one of the fastest private supercomputers in the world. (We've melted GPUs getting here.)
About the Role
We're looking for a lead-level Security Engineer and Architect to own system, network, and host security end-to-end for a rapidly growing on-prem, Kubernetes-based AI factory. This is a hands-on, high-impact role reporting directly to our CTO/CISO and working side-by-side with Technical Operations, Corp IT, Platform Engineering, and our scientific teams. It's not a compliance seat that exists to satisfy published controls &mdash; it's the chance to shape our security posture from the ground up, secure high-value client data, and build the team and tooling to do it.
Two things make this role distinctive. First, Alembic is &quot;Default to Open&quot; by design: security here must respect that maximum information sharing is basic to how we operate, while still protecting customer data and the IP &mdash; patents and trade secrets &mdash; our applied-science work generates. Balancing those is the core intellectual challenge of the job. Second, we're an AI-first company that uses many kinds of AI across everything we do; deciding which AIs operate in which containers is one of the more interesting problems you'll own.
What You'll Do<ul><li>
Design and implement security controls across all environments &mdash; network segmentation and firewalling, IDS/IPS, and traffic analysis on our on-prem Kubernetes platform.</li><li>
Build and enforce host security: EDR, kernel telemetry, hardening, and baseline implementation across the fleet.</li><li>
Own identity and access &mdash; AuthN/AuthZ, RBAC, and service identity &mdash; grounded in OIDC, SAML, and mTLS.</li><li>
Stand up incident-detection pipelines (SIEM, metrics, endpoint telemetry) tuned to surface high-signal threats over noise, and lead incident response end to end: triage, containment, recovery, root-cause analysis, and forensics.</li><li>
Keep the focus on enablement over restriction &mdash; effective security, not compliance for its own sake &mdash; while balancing IP protection, customer-data protection, and broad internal information sharing.</li><li>
Partner with Legal and the CISO to obtain the compliance certifications we need and to answer customer questions about the security of our systems; hire and mentor as the security function grows.</li></ul>
What Will Help You Succeed<ul><li>
8+ years in security engineering, infrastructure, or related roles.</li><li>
Strong Linux system security and networking (SSH certificates, directory-based authentication) and strong Kubernetes security (RBAC, tenant isolation, admission control).</li><li>
Real experience securing on-prem environments, not only public cloud.</li><li>
A proven track record leading real-world incidents, with familiarity with attacker techniques (lateral movement, persistence, exfiltration) and hands-on depth in EDR, IDS/IPS, and SIEM.</li><li>
Strong command of OIDC, SAML, mTLS, and cryptography-based storage security.</li><li>
Comfort writing code, automation, and tooling in Python or similar, plus configuration management via IaC (Terraform, Ansible).</li><li>
The judgment to distinguish high-signal threats from noise, make pragmatic tradeoffs in a fast-moving company, and communicate effectively with technical stakeholders.</li></ul>
Nice to have: high-performance or distributed-compute experience (HPC, GPU clusters); identity-aware proxies or zero-trust architectures; offensive security (red teaming, exploit development); secure application development and secure-code training; responsible-disclosure/bug-bounty programs; AI controls, MCP security, agent security, and AI governance; and a background in corporate IT security.
The role is right for you if:<ul><li>
You want to shape a security posture from first principles rather than administer someone else's control framework &mdash; and you see &quot;Default to Open&quot; as a design constraint worth solving, not a threat to route around.</li><li>
You'd rather be in the terminal doing root-cause analysis and building detection pipelines than managing them from a slide deck, and you want to build the team around you as scope grows.</li></ul>
Why You Might Be Excited About Alembic<ul><li>
Hard problems with real impact: You'll secure a one-of-a-kind on-prem AI factory and protect the high-value data behind multimillion-dollar decisions at Fortune 100 companies.</li><li>
Technical autonomy: Direct access to the CTO/CISO and decision-makers, ownership over the security architecture, and the freedom to solve problems your way.</li><li>
Cutting-edge environment: Secure our own NVIDIA DGX SuperPOD on Grace Blackwell &mdash; one of the fastest private supercomputers in the world &mdash; and take on genuinely novel work in AI, agent, and MCP security.</li><li>
Elite team: Join top engineers and scientists who thrive on hard problems, and build the security team from a front-row seat in the culture.</li><li>
Series B momentum, real ownership: Meaningful equity at a Series B company that's raised $145M, with proven product-market fit and Fortune 100 traction.</li></ul>
Why You Might Not Be Excited<ul><li>
You want a compliance-first role focused on satisfying published controls &mdash; this job is about effective security and enablement, and treats certifications as a byproduct, not the point.</li><li>
You need a fully built-out program, tooling, and process to step into, rather than the mandate to define them.</li><li>
You're uncomfortable with &quot;Default to Open&quot; &mdash; if your instinct is to lock everything down by default, the constant balance of IP protection, customer-data protection, and broad internal sharing will feel like friction rather than the interesting part.</li><li>
You prefer static over dynamic &mdash; priorities and scope shift as we grow. We have real paying customers and a playbook, and we still move at startup speed at Series B scale.</li></ul>
Compensation Range: $210K - $240K</div>

Lead Security Engineer

Ontrac Solutions

<div><h1 class="jobSectionHeader">Overview</h1>
We are seeking a Principal GenAI Architect / Forward Deployed Principal Engineer to lead the design, delivery, and productionization of enterprise-grade Generative AI solutions within a highly regulated banking environment. This role will partner directly with business, product, engineering, architecture, risk, cyber, legal, compliance, and model governance teams to translate high-impact financial services use cases into scalable, secure, and compliant AI systems.
The ideal candidate has deep experience designing and delivering production-scale GenAI solutions across enterprise environments, with strong exposure to banking, financial services, risk management, customer operations, regulatory controls, and data protection requirements. This person will serve as a recognized GenAI expert across the organization, helping define reusable patterns, influence platform roadmaps, and raise the technical bar for responsible AI adoption across lines of business.
<h2 class="jobSectionHeader">Key Responsibilities</h2>
<h3 class="jobSectionHeader">GenAI Architecture &amp; Production Readiness</h3>
Own and define enterprise-grade GenAI architectures for banking and financial services use cases, including RAG pipelines, agentic workflows, prompt orchestration, and multi-model routing strategies.
Drive production readiness for GenAI solutions, ensuring scalability, resiliency, observability, latency optimization, security, and cost efficiency.
Lead complex architectural decisions across data ingestion, vector databases, model selection, guardrails, API scalability, performance optimization, and secure integration with banking systems.
Establish reference architectures, reusable patterns, and best practices to accelerate responsible GenAI adoption across lines of business.
Partner with central AI platform teams to align solution architecture with enterprise AI services, platform capabilities, banking technology standards, and long-term roadmap priorities.
<h3 class="jobSectionHeader">Banking Use-Case Delivery</h3>
Act as a Forward Deployed Principal Engineer, partnering directly with business, product, and engineering teams to deliver high-impact GenAI use cases from ideation through production.
Translate banking and financial services business problems into clear AI system designs, technical requirements, and non-functional requirements with measurable outcomes.
Support GenAI use cases across areas such as customer service, operations, knowledge management, risk, compliance, fraud, employee productivity, document intelligence, and internal workflow automation.
Troubleshoot and resolve complex issues across non-production and production environments.
Partner closely with application teams to ensure AI solutions integrate effectively into existing banking platforms, enterprise workflows, data environments, APIs, and control frameworks.
Influence platform roadmap by feeding real-world banking use-case requirements back into central AI services and enterprise AI platform teams.
<h3 class="jobSectionHeader">Governance, Risk &amp; Compliance</h3>
Ensure all AI solutions align with banking risk, cyber, model governance, data protection, privacy, and regulatory expectations.
Partner with Cyber, Model Risk Management, Legal, Compliance, Risk, and Data Governance teams to design compliant AI patterns without slowing delivery.
Embed security, privacy, responsible AI, ethical AI, explainability, human oversight, and auditability into solution design by default.
Help define practical implementation patterns that balance innovation, speed, governance, regulatory expectations, and enterprise control requirements.
Ensure GenAI solutions are designed with appropriate guardrails for sensitive financial data, customer information, personally identifiable information, and regulated business processes.
<h3 class="jobSectionHeader">Organizational Influence &amp; Mentorship</h3>
Serve as a recognized GenAI expert across the enterprise, regularly consulted by engineering, architecture, product, risk, compliance, and leadership teams.
Mentor senior and staff-level engineers and help raise the technical bar across banking technology teams.
Contribute to internal communities of practice, architecture reviews, executive-level technical discussions, AI governance forums, and knowledge-sharing sessions.
Represent enterprise GenAI capabilities in internal innovation forums, banking technology discussions, and responsible AI showcases.
<h2 class="jobSectionHeader">Required Qualifications</h2>
7+ years of software engineering experience, with significant depth in AI/ML, data-intensive systems, distributed systems, or enterprise-scale platforms.
2+ years of hands-on Python programming experience.
2+ years of experience designing and delivering production-scale Generative AI systems in an enterprise environment.
2+ years of experience with LLMs, prompt engineering, and RAG architecture.
2+ years of experience with vector databases, semantic search, and retrieval systems.
2+ years of experience with API-driven, cloud-native architectures.
2+ years of experience with distributed systems, performance optimization, scalability, and reliability engineering.
Experience working within banking, financial services, fintech, or another highly regulated enterprise environment.
<h2 class="jobSectionHeader">Preferred Qualifications</h2>
Strong understanding of banking technology environments and non-functional requirements, including security, scalability, resiliency, observability, latency, auditability, and cost management.
Demonstrated Principal-level impact, with influence across multiple teams, platforms, business units, or lines of business.
Experience operating in highly regulated environments, with financial services or banking experience strongly preferred.
Hands-on experience with agentic AI frameworks, AI workflow orchestration, and multi-model routing.
Prior experience in a Forward Deployed Engineer, embedded engineering, or business-facing technical delivery model.
Experience partnering with risk, cyber, legal, compliance, data governance, or model governance teams to deliver production AI solutions.
Familiarity with banking controls, customer data protection, model risk management, audit requirements, regulatory expectations, and responsible AI principles.
Ability to communicate complex technical concepts clearly to senior executives, technical stakeholders, risk partners, compliance teams, and non-technical business leaders.
<h2 class="jobSectionHeader">Ideal Candidate Profile</h2>
The ideal candidate is a hands-on Principal-level engineer and architect who can move seamlessly between strategy, architecture, and execution in a banking environment. They are comfortable working directly with business teams to understand real-world financial services problems, while also going deep with engineering teams on system design, performance, security, governance, and production readiness.
This person brings strong technical judgment, enterprise banking delivery experience, and the ability to build practical, compliant GenAI solutions that can scale responsibly across a large financial institution.</div>

Principal AI Engineer

Wells Fargo

<div>About this role:
Wells Fargo is seeking a Principal Engineer to join our AI Platforms and Enterprise Execution Group as part of Consumer Technology. Learn more about the career areas and business divisions at wellsfargojobs.com.
This role focuses on designing and delivering enterprise‑scale strategic initiatives in reusable AI patterns that deliver business and customer value.
This is a hands‑on Principal Engineer role for a technical leader who designs, builds, and scales AI‑driven platforms, while operating at enterprise scope. The Principal Engineer serves as a technical authority who codes, prototypes, and reviews architecture, not just oversees execution 
In this role, you will:<ul><li>
Act as a trusted advisor to leadership, guiding the development and influence of applications, networks, information security, databases, operating systems, web technologies, and emerging AI capabilities to address highly complex business and technical needs across multiple groups</li><li>
Lead the strategy and resolution of highly complex, unique challenges through end‑to‑end solution design, including Generative and Agentic AI systems, cloud‑native platforms, and legacy modernization efforts that require long‑term vision, creativity, innovation, and advanced analytical thinking</li><li>
Translate advanced technology expertise, deep understanding of enterprise business objectives, organizational structure, and the broader technology ecosystem into scalable engineering solutions, such as reusable architectures, AI-enabled platforms, and production‑ready systems</li><li>
Provide vision, direction, and technical leadership to senior leaders on implementing innovative business solutions, embedding AI and automation into product delivery workflows, decision support, and developer productivity while ensuring alignment with security, compliance, and responsible AI standards</li><li>
Maintain deep awareness of industry best practices, emerging technologies, and AI advancements, proactively recommending innovations that modernize operations, improve efficiency and quality, and create competitive advantage for the organization</li><li>
Strategically engage with professionals and managers at all levels of the enterprise, serving as an expert technical advisor and escalation point for complex platform, data, and AI decisions while mobilizing and guiding large‑scale, cross‑organizational initiatives and communicating progress to executive leadership</li></ul> 
Required Qualifications:<ul><li>
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education</li><li>
7+ years of senior engineering experience, including architecture and hands‑on delivery of large‑scale platforms and systems</li><li>
4+ years of experience developing or deploying AI‑powered tools, chatbots, LLM‑based automation, or agentic workflows, including understanding of AI risks, observability needs, and stakeholder communication</li><li>
3+ years of hands‑on experience across Cloud architectures including Google Cloud Platform, Microsoft Azure, AWS, etc. and internal platforms such as Tachyon</li><li>
3+ years of experience operating at both keyboard‑level technical depth and executive‑level technical storytelling</li></ul>
Desired Qualifications:<ul><li>
Experience working within agile product operating models in large enterprise environments, including agile software delivery and cloud infrastructure</li><li>
Financial services experience preferred; Business Banking domain experience is beneficial but not required</li><li>
Demonstrated ability to mentor senior and staff engineers, raising the technical bar of the organization</li><li>
Proven strategic thinking, analytical problem‑solving, and sound technical judgment in fast‑paced settings</li><li>
Proven experience with cloud infrastructure and containerization, including enterprise compute, storage, and IaaS environments</li><li>
Demonstrated curiosity and innovation mindset for advancing Generative and Agentic AI solutions within regulated enterprise contexts</li><li>
Strong organizational savvy and customer centricity, with the ability to navigate complex enterprise structures and align technology to business outcomes</li></ul> 
Job Expectations:<ul><li>
Ability to travel as needed
</li><li>This position offers a hybrid work schedule</li><li>
This position is not eligible for Visa sponsorship</li></ul>
Job Location:
333 Market St - San Francisco, California 94105
300 S. Brevard - Charlotte, North Carolina 28202
2600 S Price Rd - Chandler, Arizona 85286
Pay Range 
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.
$159,000.00 - $305,000.00<div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div>
Benefits
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.<ul><li>
Health benefits</li><li>
401(k) Plan</li><li>
Paid time off</li><li>
Disability benefits</li><li>
Life insurance, critical illness insurance, and accident insurance</li><li>
Parental leave</li><li>
Critical caregiving leave</li><li>
Discounts and savings</li><li>
Commuter benefits</li><li>
Tuition reimbursement</li><li>
Scholarships for dependent children</li><li>
Adoption reimbursement</li></ul></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
Posting End Date:
12 Jul 2026<ul><li>Job posting may come down early due to volume of applicants.</li></ul>
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit&rsquo;s risk appetite and all risk and compliance program requirements.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
Drug and Alcohol Policy 
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
Wells Fargo Recruitment and Hiring Requirements:
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.</div>

Salesforce

<div>To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Software Engineering
Job Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn&rsquo;t a buzzword &mdash; it&rsquo;s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
The Experience
 
Salesforce is building the next-generation Enterprise Knowledge Graph platform to power AI-driven experiences, agentic applications, semantic search, enterprise data discovery, and intelligent decision-making across the company. The platform serves as the foundational knowledge layer connecting enterprise data, business entities, ontologies, and relationships across multiple domains.
 
 
We are seeking both a Senior Member of Technical Staff (SMTS) and a Lead Member of Technical Staff (LMTS) to join our Enterprise Knowledge Graph and AI Engineering team.
 
 
The SMTS will serve as a senior engineer and core systems developer &mdash; heavily hands-on, developing, optimizing, and scaling core knowledge graph components, semantic pipeline workflows, and AI-powered frameworks. You will partner with Lead and Principal Engineers to implement technical designs and build production-ready scalable systems that support agentic AI use cases across the enterprise.
 
 
The LMTS will serve as a hands-on technical lead, systems designer, and ontology engineer &mdash; designing, building, and scaling core knowledge graph infrastructure, semantic schemas, and AI-powered developer frameworks. You will partner closely with Principal Engineers, Product Management, Ontology experts, and Data Engineering teams to turn high-level engineering visions into production-ready scalable foundations.
 
 
Both roles will actively implement and drive AI-powered engineering tools and developer platforms that improve engineering productivity, software quality, and delivery velocity across the organization. 
 
What You'll Actually Be Doing
<ul><li>Design &amp; Implement: Build and scale Salesforce's Enterprise Knowledge Graph platform components, focusing on performance, data throughput, system reliability, high availability, and robust data integrity. (LMTS: Lead hands-on design and implementation of platform subsystems; SMTS: Write high-quality, production-grade code.)
</li><li>Graph &amp; Ontology Engineering: Develop graph data models, write complex graph queries, and construct scalable data pipelines to ingest and map structured and unstructured data to enterprise ontologies and taxonomies. (LMTS: Also design enterprise ontologies, taxonomies, semantic layers, entity resolution frameworks, graph APIs, and vector search capabilities to support advanced RAG and agentic workflows.)
</li><li>Semantic Routing: Write and maintain Python-based semantic routing frameworks to parse, classify, and dynamically direct incoming queries to the appropriate knowledge graph indexes or vector databases. (LMTS: Design, optimize, and productionize routing frameworks at enterprise scale, steering queries to appropriate knowledge graphs, ontology sub-graphs, or vector databases.)
</li><li>AI Tooling &amp; Automation: Build, integrate, and leverage AI-powered developer tools and engineering automation platforms utilizing ecosystems such as Claude, Cursor, Windsurf, AI Agents, and Model Context Protocol (MCP) frameworks. (LMTS: Also develop, deploy, and optimize these tools; drive strategy and productionization.)
</li><li>Data Integration: Build scalable data pipelines and engineering patterns to ingest, transform, and orchestrate structured, unstructured, and third-party data sources into graph-based platforms mapped tightly to enterprise ontologies.
</li><li>Feature Ownership &amp; Technical Execution: Own the technical execution of specific platform features from concept through design, coding, testing, and production deployment. (LMTS: Also translate high-level technical visions and roadmaps into concrete system blueprints, ontology schemas, and execution plans.)
</li><li>Code Quality &amp; Rigor: Participate heavily in code reviews, write comprehensive automated unit/integration tests, and ensure adherence to engineering standards and operational best practices.
</li><li>Technical Mentorship: Provide technical guidance and mentorship to engineers on the team. (SMTS: Mentor MTS and Associate engineers. LMTS: Provide day-to-day guidance, code reviews, and design direction to SMTS, MTS, and associate engineers, fostering a culture of technical rigor and operational maturity.)
</li><li>Cross-Functional Collaboration: Work closely with Lead/Principal Engineers, Product Managers, and Data Engineering teams to deliver robust features aligned with broader enterprise AI priorities. (LMTS: Also partner with PMTS engineers and Ontology governance boards to ensure alignment with AI infrastructure standards.)
</li><li>Evaluate &amp; Innovate (LMTS): Conduct deep-dive evaluations of emerging graph technologies, ontology modeling tools, semantic reasoning frameworks, vector databases, and AI tooling to continuously modernize the platform.
</li></ul>You're Our Person If...
SMTS
<ul><li>Experience: 8+ years of hands-on software engineering experience in development, data engineering, distributed systems, or enterprise data platforms.
</li><li>Education: A related technical degree required.
</li><li>Core Programming: Expert-level coding skills in backend ecosystems, with strong fluency in Python and standard object-oriented/functional programming languages.
</li><li>Semantic Routing &amp; AI: Hands-on experience developing and deploying custom semantic routers using Python (leveraging native embeddings, LangChain, or mathematical logic like cosine similarity) alongside RAG architectures, vector search platforms, and AI workflows.
</li><li>Graph &amp; Ontology Fundamentals: Solid experience working with graph databases and semantic web concepts (e.g., Neo4j, RDF/OWL, SPARQL, property graphs) and mapping data to structured taxonomies.
</li><li>Developer Tooling: Practical experience configuring, testing, or integrating AI-assisted engineering tools or automation workflows (e.g., Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks).
</li><li>Distributed Systems &amp; Cloud: Proven experience building applications on cloud-native systems (AWS, GCP, or Azure) utilizing microservices, REST/gRPC APIs, and event-driven data streaming (e.g., Kafka).
</li><li>Delivery: Track record of owning and successfully delivering complex features in an agile, production-scale environment.
</li></ul>LMTS
<ul><li>Experience: 10+ years of hands-on experience in software engineering, data engineering, distributed systems, or enterprise data platforms.
</li><li>Education: A related technical degree required.
</li><li>Ontology &amp; Graph Expertise: Solid, hands-on experience designing and building Knowledge Graph platforms, formal ontologies, semantic models, taxonomies, or enterprise metadata management systems.
</li><li>Tooling &amp; Ecosystems: Strong hands-on experience with graph technologies and ontology engineering tools (e.g., Neo4j, TopQuadrant, Prot&eacute;g&eacute;, RDF/OWL, SPARQL, SHACL, property graphs) and semantic reasoning frameworks.
</li><li>AI &amp; Retrieval: Proven experience implementing graph-powered AI solutions, vector search platforms, Retrieval-Augmented Generation (RAG) architectures, and orchestrating agentic workflows.
</li><li>Semantic Routing Mastery: Demonstrated hands-on experience designing, optimizing, and productionizing custom semantic routers using Python (leveraging native embeddings, LangChain, semantic-router, or specialized mathematical logic like cosine similarity) to decouple intent handling from expensive LLM calls.
</li><li>Developer Automation: Experience deploying and integrating AI-assisted engineering tools or automation workflows using ecosystems like Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks.
</li><li>Backend &amp; Cloud: Strong experience with cloud-native system designs (AWS, GCP, or Azure), distributed systems, microservices, and high-throughput event-driven systems.
</li><li>Leadership: Demonstrated experience leading feature teams, guiding technical execution, and mentoring mid-to-senior level engineers.
</li></ul>Even Better If...
SMTS
<ul><li>Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
</li><li>Familiarity with ontology validation frameworks (e.g., SHACL) and data quality governance.
</li><li>Experience building integrations with data platform environments like Salesforce Data Cloud or enterprise CRM metadata architectures.
</li><li>Experience optimizing low-latency applications and heavy-throughput vector search lookups.
</li><li>Passion for engineering automation and driving personal/team velocity via advanced AI development tools.
</li></ul>LMTS
<ul><li>Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field with a focus on Semantic Web or Knowledge Representation.
</li><li>Direct experience integrating platforms with Salesforce Data Cloud, CRM platforms, or metadata-driven system designs.
</li><li>Experience with semantic routing at enterprise scale, high-throughput enterprise search systems, and graph-powered recommendation engines.
</li><li>Deep familiarity with advanced ontology governance, federated knowledge management, and data contract alignment.
</li><li>Proven track record of optimizing engineering team velocity through the tailored implementation of AI developer tooling.
</li></ul>Unleash Your Potential
When you join Salesforce, you&rsquo;ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we&rsquo;ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future &mdash; but to redefine what&rsquo;s possible &mdash; for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates&rsquo; resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that&rsquo;s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications &ndash; without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.
At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.&amp;#xa;&amp;#xa;The typical base salary range for this position is $148,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $285,800 annually.&amp;#xa;&amp;#xa;The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.</div>

Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

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Data Engineer (SMTS/LMTS) - Knowledge Graph & AI