Top AI Jobs in San Francisco Bay Area, CA

Serve as the primary technical owner for strategic enterprise customers, designing and delivering agentic AI solutions on the Moveworks platform. Architect integrations with enterprise systems, build secure performant workflows, advise on AI roadmaps, collaborate across product and engineering teams, mentor peers, and generalize customer solutions into reusable templates. Regular customer-facing role with up to 25% travel.

Design and build AI-powered prototypes and end-to-end LLM workflows using Claude, ChatGPT, and other platforms. Partner with Services leaders to prioritize opportunities, translate needs into roadmaps, integrate AI with internal systems, and help productionize solutions. Create documentation, run enablement sessions, and drive adoption across Global Services while collaborating with centralized AI engineering.

Partner with Customer Success leaders to identify and prioritize AI opportunities; prototype and productize LLM-powered solutions and end-to-end workflows; integrate AI with APIs and internal data sources; develop prompts, skills, agents, and retrieval systems; enable teams via documentation, workshops, and training; and collaborate with engineering to scale prototypes into production.

Build and lead internal AI tooling and automation for security: develop threat-hunting and remediation tools, own large-scale log and ETL pipelines, maintain Kubernetes and serverless infrastructure, partner with product teams to reduce risk, and mentor junior engineers.

Design and operate scalable, event-driven backend systems in Python to power agentic AI workflows and real-time financial infrastructure. Own APIs, data architecture, reliability primitives, and platform foundations while partnering with ML and product teams to productionize AI-native financial systems.

Lead and manage an engineering team building internal AI-powered security tooling and automation. Own delivery, roadmap, and infrastructure (Kubernetes, serverless, ETL/log pipelines). Build tools for incident response, threat hunting, and remediation, partner with product teams to reduce risk, mentor engineers, and drive AI-driven solutions at scale.

Design, build, and deploy production AI agents and orchestration systems using tools like LangChain and LlamaIndex. Apply prompting, RAG, fine-tuning, and model selection. Architect agent reasoning and workflows, implement monitoring and evaluation, and integrate AI systems with backend and frontend services for scalable, reliable, compliant production deployments.

Design and operate scalable, event-driven backend systems in Python for AI-native financial products. Build typed APIs (FastAPI + Pydantic), own data and ledger architectures, develop reliability primitives, partner with ML teams to productionize models, and ship platform foundations for audited, high-throughput financial workflows.

Build and lead internal AI-driven security tooling and automation, support incident response with threat-hunting tools, maintain Kubernetes/serverless and ETL/log pipelines, partner with product teams to reduce risk, and mentor engineers.

Design and deploy agentic AI systems that automate multi-step financial workflows. Architect agents using frameworks like LangChain and LlamaIndex, apply prompting, RAG, and fine-tuning, optimize reasoning and tool use, build feedback-driven systems, and integrate AI reasoning securely into production backend and frontend services.

Build and scale core AI platform primitives and integrations to enable rapid, safe AI product development. Own infrastructure, shared libraries, APIs, observability, and reliability systems; operate production AI systems, debug provider/model behavior, and implement versioning, rollout controls, and quality gates to minimize user disruption.

Design and ship AI agents and automation for GTM workflows. Conduct stakeholder research, embed in field rhythms, own system architecture, reliability, adoption, and iterate to drive measurable revenue impact.

As a Staff AI Engineer at Fieldguide, you will define technical direction, build AI systems, mentor engineers, and drive organizational leverage across various teams, while focusing on enterprise-grade reliability.

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

As an AI Engineer at Fieldguide, you'll develop AI agents for complex audit workflows, design systems for reliability, and optimize agent capabilities based on customer needs. You'll build and integrate systems using LLMs and ensure agents improve over time, collaborating closely with product and design teams.

As an AI Engineer, you will create a unified evaluation infrastructure for AI agents, ensuring reliable performance while integrating automated pipelines and feedback systems for rapid model evaluation and quality assurance.

Responsible for developing and enhancing an AI SDK, ensuring high performance and integration with deployment platforms, while collaborating with cross-functional teams and engaging with the open-source community.

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.

Build and enhance AI applications for enterprises, focusing on frontend development using modern technologies like Next.js and React. Collaborate with teams to create intuitive user experiences and optimize UI performance.

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.

The Senior Applied Research Engineer will focus on improving AI systems through experimentation and research, collaborating with engineering teams to implement findings into production systems.

Owner of end-to-end AI-first marketing: research customers and product, craft positioning and narratives, create assets (case studies, videos, landing pages, decks), ship rapidly using AI, distribute and measure performance, and iterate to drive product and customer storytelling.

As Principal Product Manager, AI, you will define and execute the AI strategy at Drata, leading the development of AI-native experiences, collaborating with cross-functional teams, and driving the AI product vision while mentoring other product managers.

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.