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principal engineer platform engineering

Cisco

The application window is expected to close on: 09/11/2026Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
 
Meet the Team
 The Platform Engineering organization is responsible for building and operating the foundational cloud-native platforms that power engineering across Cisco Network Platform. Our team owns the Kubernetes ecosystem used by thousands of developers, spanning hundreds of clusters across public and on-premise environments.. We provide the infrastructure, automation, observability, security, and self-service capabilities that enable product teams to build and operate services reliably at scale.
 We are a highly collaborative team of SREs, who enjoy solving complex distributed systems challenges. Our culture emphasizes ownership, operational excellence, automation, and continuous improvement. This is an opportunity to shape the future of Kubernetes and platform engineering within Cisco Network Platform while influencing the experience of engineers across the company.
 Your Impact
 Architect and drive the evolution of Kubernetes platform strategy across cloud and on-premises environments supporting mission-critical workloads at scale.
 Lead the design and implementation of platform capabilities that improve reliability, security, scalability, and developer productivity for hundreds of engineering teams.
 Partner with engineering, security, and product leaders to define multi-year platform roadmaps and drive execution of company-critical initiatives.
 Provide technical leadership during major incidents, architecture reviews, platform transformations, and strategic infrastructure investments.
 Mentor senior engineers and help raise the engineering bar through technical leadership, design reviews, operational excellence, and architectural guidance.
 
Minimum Qualifications
 
<ul>
<li>15+ years of experience designing, building, and operating large-scale distributed systems in production environments.</li>
<li>7+ years of hands-on experience operating Kubernetes platforms in production, including multi-cluster environments.</li>
<li>Experience architecting and operating cloud-native infrastructure across AWS, Azure, GCP, or hybrid cloud environments.</li>
<li>Experience designing, operating, and troubleshooting networking architectures for large-scale Kubernetes platforms, including CNI implementations, ingress and egress traffic management, service-to-service communication, multi-cluster connectivity, and network observability.</li>
<li>Experience with Infrastructure-as-Code and GitOps technologies, including Terraform and ArgoCD or equivalent platforms.</li>
<li>Strong communication and leadership skills with the ability to effectively influence engineers, architects, senior leaders, and executive stakeholders.</li>
<li>Proven track record leading cross-organizational platform initiatives and influencing technical strategy across multiple engineering teams.</li>
<li>Experience implementing SRE practices, including SLOs, incident management, production readiness reviews, and operational excellence programs.</li>
<li>Strong software engineering experience with Go, Python, or similar programming languages used for automation and platform development.</li>
</ul>
Preferred Qualifications
 
<ul>
<li>Experience with migrating monolithic applications to a microservices architecture.</li>
<li>Knowledge of networking (i.e. switching, routing, wifi, IoT).</li>
</ul>
Why Cisco?
 
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
 Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
 We are Cisco, and our power starts with you.
 
Message to applicants applying to work in the U.S. and/or Canada:
 
The starting salary range posted for this position is $231,400.00 to $331,800.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
 Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.
 
U.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.
 
U.S. employees are eligible for paid time away as described below, subject to Cisco’s policies:
 
<ul>
<li>10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees</li>
<li>1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco</li>
<li>Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees</li>
<li>Exempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)</li>
<li>80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next</li>
<li>Additional paid time away may be requested to deal with critical or emergency issues for family members</li>
<li>Optional 10 paid days per full calendar year to volunteer</li>
</ul>
For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies.
 
Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:
 
<ul>
<li>.75% of incentive target for each 1% of revenue attainment up to 50% of quota;</li>
<li>1.5% of incentive target for each 1% of attainment between 50% and 75%;</li>
<li>1% of incentive target for each 1% of attainment between 75% and 100%; and</li>
<li>Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.</li>
</ul>
For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.
 
The applicable full salary ranges for this position, by specific state, are listed below:
 
New York City Metro Area: 
$231,400.00 - $381,600.00
 
Non-Metro New York state& Washington state: 
$222,900.00 - $343,600.00
 <ul>
<li>For quota-based sales roles on Cisco’s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.</li>
</ul>
** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.

Principal Engineer - Platform Engineering

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

Hellyeah AI

AI Engineer - Learn Engine: Intelligence &amp; OptimizationLocation: San Francisco HQ; ShanghaiAddress: San Francisco, CaliforniaEmployment Type: Full timeLocation Type: HybridDepartment: EngineeringCompensation: San Francisco $200K - $1M + 0.5% - 3% equityBuild the brain of an autonomous growth OS. The system you create will manage millions in ad spend and get measurably smarter with every dollar. This is the moat: every competitor has humans optimizing campaigns manually. You are building the intelligence layer that compounds. The Platform engineer creates the tools; you create the decisions. Together you build something nobody else has.Must Have- Has built recommendation, optimization, or decision systems where outputs improve future inputs.- Strong statistical reasoning and experimentation judgment under noisy real-world data.- Strong LLM orchestration or agent-system experience for reasoning over campaign context.- Can design optimization policies, scoring systems, or automated recommendation loops.- AI-first development workflow and ability to ship production systems quickly.Nice to Have- Ad-tech optimization patterns: bid management, budget allocation, ROAS optimization.- Reinforcement learning experience.- Hyperparameter optimization experience.- Model fine-tuning experience.- Experience building agent-driven automation where LLM agents take actions.- Background in growth engineering, performance marketing, or data science.- Experience with Mastra or similar agent orchestration framework.What You Will OwnOwn the intelligence and optimization layer of Learn Engine. Build recommendation engines for bid changes, budget reallocation, pause/boost decisions, and postback optimization. Turn SSOT campaign data into high-quality optimization guidance and closed-loop decision systems. Define how the system learns from outcomes and continuously improves campaign strategy over time. This role owns decision quality, optimization policy, and learning loops, not platform plumbing or simulator infrastructure.Pay: $200,000.00 - $1,000,000.00 per yearWork Location: In person

AI Engineer - Learn Engine: Intelligence & Optimization

Heygen

<div><div><h2 class="jobSectionHeader">About HeyGen</h2>

At HeyGen, our mission is to make visual storytelling accessible to all. Over the last decade, visual content has become the preferred method of information creation, consumption, and retention. But the ability to create such content, in particular videos, continues to be costly and challenging to scale. Our ambition is to build technology that equips more people with the power to reach, captivate, and inspire audiences. 
Learn more at www.heygen.com. .</div><div>
Position Summary

As a Security Engineer at HeyGen, you will own the security posture of one of the fastest-growing AI companies in the world. You will partner directly with engineering teams to ship secure features, harden our cloud infrastructure, and build the compliance and trust programs that unlock enterprise deals. This is a high-impact, high-autonomy role for an engineer who thinks in threat models and ships code.

Key Responsibilities
<ul>
<li>Product &amp; Infrastructure Security: Partner with engineering teams as an embedded security expert &mdash; writing code, reviewing architectures, and building secure application features and infrastructure components from the ground up.</li>
<li>Fraud Detection &amp; Remediation: Design and implement automated fraud detection systems to mitigate platform abuse, credential stuffing, and payment fraud. Partner with product and engineering to build real-time monitoring and rapid-response remediation workflows.</li>
<li>Cloud &amp; Vulnerability Management: Own the strategy and execution for hardening our AWS/Python infrastructure. Build and run a robust vulnerability management program, including network security, cloud configuration, and remediation workflows.</li>
<li>AI Security: Serve as HeyGen's point person for AI and agentic system security. As we scale our agentic coding and AI agent products, you will ensure these rollouts are designed and deployed with strong security controls.</li>
<li>GRC &amp; Compliance: Oversee our SOC 2 compliance operations (currently managed via Drata) and annual audit cycles. Evaluate and roadmap future certifications, including ISO 27001, as the business scales.</li>
<li>Trust &amp; Safety Oversight: Provide high-level oversight for platform abuse and content moderation (in partnership with growth and avatar teams), and serve as the escalation point for IT security incidents.</li>
</ul>
Qualifications
<ul>
<li>Strong software engineering background with hands-on Python and AWS experience; you write code, not just policies.</li>
<li>Demonstrated experience securing cloud infrastructure and applications &mdash; vulnerability management, network security, IAM, and secrets management.</li>
<li>Familiarity with GRC frameworks and compliance programs (SOC 2, ISO 27001, or equivalent).</li>
<li>Excellent communication skills: able to translate threat models for engineers, compliance requirements for auditors, and security architecture for enterprise CISOs.</li>
<li>Comfortable with ambiguity and rapid scale; you prioritize ruthlessly and know when to build vs. buy.</li>
<li>Experience with modern security tooling is a plus (Drata, Infisical, Bugcrowd, or equivalents).</li>
</ul>
Why HeyGen:
<ul>
<li>Massive Scale, Unique Problems: We are protecting user identity at one of the fastest growth rates in SaaS history. The security engineering challenges here are genuinely novel.</li>
<li>Speed with Guardrails: Our security philosophy is not about saying &quot;no.&quot; It is about building guardrails that let the engineering team ship fast without introducing unacceptable risk.</li>
<li>Mature Tooling from Day One: We already run Drata for GRC, Infisical for secrets management, and a private bug bounty program via Bugcrowd. You are not starting from zero.</li>
<li>Autonomy and Ownership: You will have the visibility and resources to shape HeyGen's entire security roadmap. Small team, big mandate.</li></ul></div></div>

Security Engineer

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

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