senior deployment engineer

DigitalOcean

<div><div>Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you'll find your place here. We value winning together&mdash;while learning, having fun, and making a profound difference for the dreamers and builders in the world.</div>
At DigitalOcean, Senior Deployment Engineers play a critical role in building and scaling the physical infrastructure that powers our cloud platform. Our Deployment team is responsible for new data center builds, infrastructure expansions, hardware deployments, cabling validation, site readiness, and repeatable execution standards that enable DigitalOcean to grow quickly and reliably.

From leading deployment workstreams to validating infrastructure readiness, driving contractor execution, troubleshooting complex blockers, and training local teams, our Senior Deployment Engineers operate across the full deployment lifecycle. You'll join a collaborative, fast-moving team with opportunities to support large-scale deployments, new data center expansions, and next-generation infrastructure.
<h3 class="jobSectionHeader">
This role requires significant onsite deployment support and requires very high levels of domestic and international travel based on project needs.</h3>
<h2 class="jobSectionHeader">What You'll Be Doing</h2>
<ul><li>Leading deployment workstreams for new data center builds, expansions, hardware rollouts, rack buildouts, cluster deployments, and high-density compute infrastructure</li>
<li>Acting as a senior onsite deployment resource for build quality, infrastructure validation, cabling validation, training, and site readiness</li>
<li>Validating vendor and contractor rack and stack work against DigitalOcean design standards, rack elevations, cabling plans, labeling requirements, and deployment procedures</li>
<li>Verifying physical readiness, including power feeds, redundancy, load balancing, rack layout, hardware placement, cable routing, labeling, and infrastructure documentation</li>
<li>Validating front-end and back-end cabling against design, port mapping, LLDP output, link checks, and internal validation workflows</li>
<li>Running and interpreting LLDP checks, automation scripts, tooling outputs, logs, and hardware diagnostics to confirm connectivity and deployment readiness</li>
<li>Identifying and driving correction of miswires, optic issues, link inconsistencies, communication errors, hardware faults, provisioning blockers, and physical layout issues</li>
<li>Troubleshooting complex issues across hardware, cabling, network-adjacent systems, Linux OS, tooling, and site conditions during high-pressure deployment windows</li>
<li>Coordinating contractors, vendors, and internal employees in a project capacity to complete assigned deployment workstreams</li>
<li>Sequencing work, assigning tasks, validating quality, tracking progress, and escalating blockers for assigned deployment areas</li>
<li>Training new DigitalOcean engineers, local Data Center Operations teams, vendors, and contractors on rack and stack standards, cabling patterns, validation workflows, and basic troubleshooting</li>
<li>Maintaining and improving deployment runbooks, validation workflows, operational procedures, checklists, and handoff documentation</li>
<li>Updating and validating DCTrack, NetBox handoff requirements, asset records, inventory systems, and deployment documentation</li>
<li>Providing daily status updates for assigned workstreams, including progress, risks, blockers, vendor issues, and recommended mitigation steps</li>
<li>Partnering with Data Center Operations, Network Engineering, Infrastructure Engineering, Logistics, Facilities, Security, Procurement, and vendors to drive deployment readiness</li>
<li>Supporting operational readiness and handoff for newly deployed infrastructure</li>
<li>Participating in lessons learned and driving improvements that reduce repeat issues across future deployments</li>
<li>Supporting planning and preparation for upcoming deployments during offsite periods</li>
</ul><h2 class="jobSectionHeader">What You'll Add to DigitalOcean</h2>
<ul><li>4+ years of experience deploying, operating, or supporting infrastructure in large-scale data center, cloud, lab, networking, or technical operations environments</li>
<li>Strong understanding of data center infrastructure, including compute, networking, storage, GPU hardware, cabling, power, rack layouts, and physical deployment standards</li>
<li>Experience deploying and troubleshooting high-density compute platforms, GPU infrastructure, and related hardware</li>
<li>Experience working with or supporting liquid-cooled infrastructure preferred</li>
<li>Strong Linux knowledge and command-line experience, including familiarity with bash scripting, logs, and diagnostic workflows</li>
<li>Strong troubleshooting skills across hardware, cabling, Linux OS, network connectivity, optics, provisioning, and tooling</li>
<li>Strong understanding of data center cabling plans, port mapping, front-end and back-end network patterns, labeling standards, and deployment best practices</li>
<li>Ability to lead assigned deployment workstreams independently in ambiguous, high-cadence environments</li>
<li>Ability to direct contractors and vendors professionally, validate completed work, correct quality issues, and drive task completion</li>
<li>Ability to evaluate deployment issues, identify root cause, leverage data, and drive timely resolution</li>
<li>Ability to communicate clearly with leadership and cross-functional partners regarding status, risk, blockers, and recommended next steps</li>
<li>Ability to update, review, and improve deployment documentation, runbooks, validation workflows, and operational procedures</li>
<li>Experience training and developing junior engineers, local site teams, vendors, and contractors</li>
<li>Ability to operate and navigate effectively through ambiguity while maintaining safety, quality, and execution standards</li>
<li>Strong ownership mindset with the ability to see deployment issues through to resolution</li>
<li>Ability to identify repeat deployment issues and recommend scalable process, tooling, or documentation improvements</li>
<li>The ability to travel domestically and internationally based on deployment needs</li>
<li>Support deployment schedules that include extended onsite periods, non-standard hours, or project-based rotations</li>
<li>Valid driver's license and comfort with driving as needed</li>
<li>Ability to remain on your feet throughout the workday</li>
<li>Ability to lift objects up to 50 lbs</li>
</ul><h2 class="jobSectionHeader">Compensation Range:</h2>
<ul><li>$105,600 - $132,000</li>
</ul>
<ul><li>This is a onsite role</li></ul>

JR: 2026-8035

#LI-Onsite<div><h2 class="jobSectionHeader">
Why You'll Like Working for DigitalOcean</h2>
<ul><li>We innovate with purpose. You'll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.</li>
<li>We prioritize career development. At DO, you'll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.</li>
<li>We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.</li>
<li>We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.</li>
<li>DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.</li>
</ul>
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.</div></div>

Senior Deployment Engineer

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

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>

Airbyte

<div>Airbyte is the data and action layer for AI agents. We give agents fast, accurate, authenticated access to business data across hundreds of sources, so they can discover the entities that matter, reason over real-time context, and take action in the systems they read from, not just observe them.
We started as the open-source standard for data movement and proved the economics of data integration at scale: hundreds of connectors, thousands of companies, and, since 2020, have raised $181M from leading investors including Benchmark, Accel, Altimeter, Coatue, and Y Combinator. As our CEO Michel Tricot puts it, &quot;the last ten years were all about structured data. The future is all about context.&quot; We're now building that context infrastructure for production-grade agents on the same open foundation, as agents become the primary consumers of enterprise data.
Our mission is unchanged: make data available and actionable to everyone, everywhere. That everyone now includes AI agents.<h2 class="jobSectionHeader">
Engineering Hiring Sprint:</h2>
We're growing our engineering team and are accelerating hiring through a focused Engineering Hiring Sprint. Rather than stretching interviews over several weeks, we're bringing exceptional candidates through an expedited process and making hiring decisions quickly.
Interview process:<ul><li>
Apply</li><li>
Technical Take-Home (Java or Python)</li><li>
Hiring Manager Interview</li><li>
In-Person Onsite (the week of July 20)</li><li>
Hiring decision by the end of the week</li></ul>
We're hiring across multiple engineering teams, including:<ul><li>
Platform Engineers</li><li>
Database Engineers</li><li>
Site Reliability Engineers</li><li>
Extensibility API Engineers</li><li>
AI Agents Engineers</li><li>
Engineering Managers</li></ul>
If you enjoy solving complex technical problems, moving quickly, embracing AI, and taking ownership of your work, we'd love to meet you.<h2 class="jobSectionHeader">
The Role:</h2>
Airbyte is looking for an Engineering Manager, Platform to lead the team responsible for the infrastructure, tooling, and engineering systems that power Airbyte Cloud, Airbyte Flex, and Airbyte Agents.
As an Engineering Manager on the Platform team, you'll lead the engineers responsible for cloud infrastructure, deployment systems, CI/CD, observability, reliability, and the internal tooling that powers engineering velocity across the company. Your work directly shapes both how fast engineers ship and how customers experience Airbyte. This isn't a keep-the-lights-on role. You'll make real tradeoffs between engineering velocity, customer-facing reliability, and long-term architecture every week, and you'll help define how AI transforms the way we build and operate software.
This role combines people leadership, technical strategy, operational excellence, and platform thinking. You'll help define how engineering works at Airbyte - not just what we build.<div> 
</div><h2 class="jobSectionHeader">
What You&rsquo;ll Do:</h2><ul><li>
Lead, mentor, and grow a team of Platform Engineers, Fullstack Engineers, and SREs. Recruit engineers who understand that infrastructure decisions are product decisions.</li><li>
Own the reliability and operational health of Airbyte's production systems.</li><li>
Define the roadmap for Airbyte's platform: infrastructure, CI/CD, deployment automation, observability, internal tooling, and the product surfaces built on top of them.</li><li>
Invest in and drive adoption of AI-powered workflows for debugging, release validation, infrastructure management, and developer productivity, moving past experimentation into real operational leverage.</li><li>
Lead incident response, run blameless postmortems, and ensure systemic fixes follow every outage. Continuously reduce operational toil through automation.</li><li>
Build leverage: a week-long task this year should take ten minutes next year.</li></ul><div> 
</div><h2 class="jobSectionHeader">
Success Metrics:</h2><ul><li>
Engineers deploy with confidence and ship faster quarter over quarter.</li><li>
Platform reliability improves as measured by customer-facing SLAs, not just internal dashboards.</li><li>
Operational toil decreases through automation, not heroics.</li><li>
Incidents are detected faster, resolved faster, and the same failure doesn't happen twice.</li><li>
Your team is engaged, growing, and building careers they're proud of.</li></ul><div> 
</div><h2 class="jobSectionHeader">
What You&rsquo;ll Need:</h2><ul><li>
5+ years of software engineering experience, 2+ years managing engineering teams.</li><li>
Experience leading Platform Engineering, Infrastructure, SRE, or Developer Productivity organizations.</li><li>
Strong understanding of cloud infrastructure, CI/CD, observability, and distributed systems.</li><li>
Experience operating production systems at scale.</li><li>
You think about platform work in terms of customer impact, not just engineering elegance.</li><li>
You've navigated the tension between paying down tech debt and shipping product, and you can articulate how you made those calls.</li><li>
Excellent communication skills. You can translate platform strategy into language that product, design, and business leaders understand.</li><li>
You have an insatiable desire to ship.</li></ul><h2 class="jobSectionHeader">
Nice To Have:</h2><ul><li>
Experience with AI-assisted engineering workflows or agentic software development.</li><li>
Experience building internal developer platforms.</li><li>
Familiarity with Terraform, Helm, Kubernetes, GitHub Actions, and cloud-native infrastructure.</li><li>
Experience with data infrastructure, ETL/ELT, or large-scale distributed systems.</li><li>
Experience contributing to open-source engineering organizations.</li><li>
Familiarity with Airbyte, connector ecosystems, or developer tooling platforms.</li></ul><div> 
</div><h2 class="jobSectionHeader">
Why This Role Matters:</h2>
Platform Engineering is the force multiplier for every engineering team at Airbyte.
Your mission is to build the systems, tooling, and infrastructure that enable engineers to move faster while making our platform more reliable, secure, and scalable. Success means every deployment becomes safer, every incident becomes easier to resolve, every engineer becomes more productive, and AI becomes a natural part of how software is built.
The best platform teams are invisible&mdash;they make everyone else dramatically more effective. That's the team you'll build.<h2 class="jobSectionHeader">
Location:</h2><ul><li>
Onsite 4 days/week in San Francisco, CA</li></ul><h2 class="jobSectionHeader">
Why You'll Love Working at Airbyte:</h2>
At Airbyte, we believe great work happens when people feel supported, trusted, and empowered to grow. Our market-leading Total Rewards package is designed to help you thrive professionally and personally. Our benefits and perks include:<ul><li>
Flexible PTO with a culture that encourages at least 25 days off annually</li><li>
16 weeks fully paid parental leave for all parents</li><li>
Comprehensive medical, dental, and vision coverage for employees and dependents</li><li>
401(k) retirement plan</li><li>
Professional development budget, conference sponsorship, and book reimbursement</li><li>
Commuter benefits and monthly internet reimbursement</li><li>
Breakfast and lunch in our San Francisco office</li><li>
A collaborative, in-person culture focused on learning, growth, and impact</li></ul>
If you find this role exciting, we encourage you to apply even if you think you don&rsquo;t meet all of the requirements!
We are not accepting agency submissions or recruiting firm support for this role. Unsolicited resumes will not be considered.
Airbyte is an equal opportunity employer that does not discriminate on the basis of actual or perceived race, creed, color, religion, national origin, ancestry, age, physical or mental disability, pregnancy, genetic information, sex, sexual orientation, gender identity or expression, marital status, familial status, domestic violence victim status, veteran or military status, or any other legally recognized protected basis under federal, state or local laws. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Airbyte is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. Please let us know if you need assistance or accommodations due to a disability.
Compensation Range: $217K - $282K</div>

Engineering Manager, Platform - Hiring Sprint

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