Top AI Jobs in San Francisco Bay Area, CA

Support global cash management, bank account administration, payments, FX exposure and hedging, investment portfolio oversight, SOX and FBAR compliance, audit support, and treasury reporting (Trovata). Coordinate with cross-functional teams and external banks to maintain liquidity, controls, and accurate treasury records.

As a Staff Product Manager, you'll drive the strategy and success of SIEM products, collaborating with various teams to fulfill customer needs and market demands while focusing on security for SMBs.

Lead and operationalize GitLab's Internal Audit function: plan and execute risk-based audits, oversee SOX testing, facilitate enterprise risk management, coach a distributed audit team, implement QA/improvement programs, and report to senior leadership and the Audit Committee.

The Senior Solutions Engineer partners with account teams to solve enterprise customer problems, deliver product expertise, and lead value-based demonstrations to drive sales success.

Provide full‑stack product legal counsel across the product lifecycle for cloud and AI products: assess privacy, security, IP, export and open‑source risks; draft and negotiate commercial and data protection agreements; support incident response and regulatory investigations; create scalable legal playbooks and tooling; advise on US/global privacy and emerging AI regulations.

Lead and execute audits of financial statements and internal controls for digital assets, assess governance and regulatory compliance, apply advanced auditing and technical accounting skills, direct and coach audit teams, communicate findings to clients, and uphold professional and independence standards.

Lead design and implementation of Microsoft Dynamics 365 solutions, supervise and mentor teams, manage project delivery, translate complex requirements into technical designs, handle data migrations and integrations, and build strong client relationships while improving service delivery.

The Senior Lead AI Engineer will develop and support AI software components, lead cross-functional teams, and optimize AI solutions for Capital One's banking systems.

Lead AI Engineer responsible for developing AI software components, partnering with cross-functional teams to deliver AI-driven products, and optimizing large-scale AI systems.

The Senior Lead AI Engineer will develop AI software components, partner with cross-functional teams, and contribute to AI system optimization. Key responsibilities include model training, deployment, and leveraging AI technologies to enhance banking services.

The Lead AI Engineer will design, develop, and support AI software components, optimizing AI systems for performance and scalability while collaborating with cross-functional teams.

The Senior Lead AI Engineer will develop, test, and support AI software, design new models, and enhance AI product offerings at Capital One while collaborating across teams.

The Applied Researcher I will partner with cross-functional teams to develop AI-powered products, conduct applied research, and build AI foundation models using emerging technologies.

The Director of Data & AI Partnerships is responsible for developing account strategies, cultivating partnerships with pharma/biotech clients, and driving revenue goals while ensuring delivery on strategic objectives.

The Senior AI Product Engineer will develop and optimize AI product features, ensuring a seamless user experience through collaboration with engineering teams. Responsibilities include building full-stack features, implementing user feedback mechanisms, and monitoring product performance.

Lead Benchling's strategic AI partnerships with model labs, scientific AI providers, and infrastructure partners. Structure and close deals for data licensing, product integrations, and co-development; build a repeatable partnerships playbook; source and diligence next-generation AI/ML companies and represent Benchling to senior external stakeholders.

Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.

Lead development of AI-powered patient experiences: LLM-driven intake and therapist matching, between-session support, evaluation and safety infrastructure, outcome measurement, and HIPAA-compliant product delivery. Partner with Engineering, ML, Data Science, Clinical, and Legal to ship and monitor models in production, write evals, design red-teaming and human-in-the-loop flows, and measure patient outcomes.

The AI Engagement Manager will lead strategic relationships with institutional owners to harness AI, improve asset performance, and drive measurable ROI across real estate portfolios.

Lead product strategy and commercialization for AI-focused software within Internal Firm Services. Drive innovation, market and competitive analysis, TAM assessment, go-to-market planning, and portfolio management. Set strategic direction, maintain executive client relationships, mentor teams, and validate revenue potential to support investment and commercialization decisions.

Lead development and implementation of AI legal and compliance frameworks. Conduct cross-functional AI reviews, maintain governance docs (model cards, impact assessments), partner with engineering on transparency and fairness requirements, build incident response and monitoring processes, and scale AI legal review workflows.

Plan and execute AI and developer-focused events and content, coordinate cross-functional teams and vendors, manage onsite speaker experience and event operations, maintain event tools and website, track deliverables, mitigate risks, and improve processes to scale community and advocacy programming.

Lead technical customer engagements to design, integrate, and launch AI-driven solutions on the Moveworks Platform. Build secure integrations (APIs, iPaaS, serverless), advise on agentic AI roadmaps, drive adoption across enterprise customers, and feed product/engineering with field feedback. Travel to customer sites up to 25% and generalize solutions into reusable templates.

Design, build, optimize, deploy, and support large-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, observability). Partner with cross-functional teams, introduce LLM optimization techniques, and contribute to technical vision and roadmap for foundational AI infrastructure.

Lead design, implementation, and deployment of end-to-end AI/ML systems for healthcare data. Drive architecture, mentor engineers, partner with cross-functional teams, and manage full ML lifecycle from data ingestion and agent development to production deployment, monitoring, and CI/CD. Emphasizes responsible AI, scalability, and operational excellence for generative and agentic AI solutions.