Top AI Jobs in San Francisco Bay Area, CA

The role involves designing and building AI agents for audit workflows, owning product areas end-to-end, and mentoring other engineers.

Lead and conduct ML research aligned to Sprinter Health's strategy: define research agenda, design rigorous experiments, develop novel methods and evaluations, publish and patent findings, translate research into production-ready tools, and collaborate with clinicians and cross-functional teams to validate and deploy clinically robust AI solutions.

The AI Strategy Consultant will design and execute research experiments, improve data quality, and collaborate with ML scientists to advance AI innovations.

The Senior Platform AI Engineer will develop production infrastructure for AI features, focusing on server architecture, agent orchestration, and AI model lifecycle management. The role requires building efficient systems and collaborating with various engineering teams to optimize workflow and enhance deployment processes.

Design, build, and scale production LLM, retrieval, and agentic AI systems for compliance automation. Implement evidence-grounded, explainable workflows, optimize for latency/cost/reliability, and embed human-in-the-loop guardrails while collaborating cross-functionally.

Lead the development and deployment of AI-powered products with a focus on foundational AI systems, LLM optimization, and team collaboration to enhance user experiences in banking.

As a Lead AI Engineer at Capital One, you will design and support AI software, develop LLM and optimization techniques, and collaborate with cross-functional teams to innovate AI products.

As a Senior Lead AI Engineer, you will design, develop, and optimize AI systems while collaborating with a cross-functional team to implement AI-driven products.

As a Lead AI Engineer, you will design and develop AI components, collaborate across teams, improve performance, and contribute to Capital One's AI vision.

The Senior Lead AI Engineer will design and develop AI-driven products, enhance scalable AI systems, and collaborate with cross-functional teams.

Lead design, build, and deploy production-scale generative AI and agentic systems: foundation model training, LLM inference, vector search, guardrails, evaluation, observability, and performance optimization across cloud infrastructure.

Design, research, implement, and deploy scalable deep learning, LLM and generative AI solutions (including RAG and fine-tuning). Advance Responsible AI practices, set research agenda, and collaborate with engineers and scientists to improve model capabilities and reliability.

Lead strategy, roadmap, and execution for AI-powered fintech products. Own end-to-end product lifecycle, mentor product managers, build ML/LLM-driven experiences (copilots, chatbots, recommendations), drive PLG and automation for growth, ensure responsible AI and compliance, and launch products across regions.

Lead strategy and roadmap for AI Access products that let publishers control agent access, deliver specs and launches, partner with engineering, design, research, GTM, and BD, and represent the product externally to publishers, AI labs, and developers.

The Senior AI Product Engineer will develop AI features integrated into products, focusing on user experience, full-stack development, and collaboration with AI engineers, product managers, and design teams.

The Applied Research Engineer will enhance AI systems through research and experimentation, focusing on information retrieval and reasoning strategies, collaborating with engineering teams to transition validated methods into production.

Lead development of AI-powered features and scalable agent infrastructure for Hex. Partner with Research on model prompting, build experimentation tooling, and deliver performant full‑stack user experiences using web and backend systems. Mentor engineers and drive major product initiatives.

Lead product strategy and execution for enterprise AI/ML and Generative/Agentic AI platforms. Drive capabilities for model training, serving, and developer/data scientist UX, partner across platforms, and deliver business value and adoption at scale.

In this role, you will design and deploy advanced machine learning and Generative AI solutions, leading projects from conception to deployment while mentoring junior team members.

The AI Engineering Specialist will oversee project tasks, manage expectations, mentor junior members, and design scalable AI systems while working with advanced AI models and ML pipelines.

The Distinguished Architect will provide technical leadership in AI, guide infrastructure discussions, and collaborate with stakeholders on AI observability solutions, requiring extensive experience and strategic thinking.

Partner with CEO/CFO to deliver executive-grade data, own global forecasting engine, build causal inference and time-series models, drive generative AI strategy and production, and scale a data science and engineering team to inform capital allocation and long-range planning.

Lead Rapid7's multi-year AI strategy and roadmap across product and operations, build and run a high-performing AI organization, drive LLM, generative and agentic capabilities, integrate threat intelligence for security detection and prioritization, establish MLOps and responsible AI governance, and represent Rapid7 externally while partnering with Sales, SOC, and Customer Success to deliver measurable business outcomes.

Design and build scalable AI platform capabilities to enable multi-step GenAI workflows, model execution, and integrations. Implement backend services, execution infrastructure, APIs, and observability to support production GenAI experiences across sales and product teams. Collaborate with AI engineers, data scientists, and product partners to turn AI use cases into reliable, extensible platform features.

Lead Headway's AI platform vision and roadmap, own the internal assistant Eddy, write evals and prompts, configure agents and integrations, and partner with CX, Ops, Sales, Finance, and Clinical teams to identify high-value AI workflows and drive adoption across the company.