Top AI Jobs in San Francisco Bay Area, CA

As a Senior Manager in Data and Analytics Engineering at PwC, you'll design data architecture strategies for healthcare, mentor teams, influence stakeholders, and enhance healthcare operations through data solutions.

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.

As a Senior AI Community Engineer, you'll engage developers through in-person events, manage community health, track participant activations, and establish Deepgram's presence in the Bay Area tech scene.

The AI Engineer will focus on building AI experiences, deploying models, and enhancing data workflows, working on greenfield applications. Key responsibilities include feature development, architecture collaboration, and shipping impactful product experiences.

As an AI Engineering Lead, you will build and lead a high-performing AI engineering team, define AI engineering functions, and collaborate to enhance product capabilities using cutting-edge AI technologies.

Lead end-to-end research and deployment of foundation models, LLMs, and agentic AI systems. Drive model development, rigorous evaluation, production transfer, collaboration with cross-functional teams, and publication of research while ensuring regulatory alignment and scalable engineering practices.

Customer-facing technical lead owning end-to-end implementations of Moveworks AI solutions for enterprise customers. Architect integrations, design secure automations, drive adoption across multiple engagements, advise on agentic AI roadmaps, and relay product feedback while creating reusable templates and upskilling customer teams.

Customer-facing senior technical lead owning end-to-end enterprise implementations on the Moveworks platform. Architect and build LLM-based solutions and secure integrations (ServiceNow, Workday, Okta, etc.), drive adoption across multiple customers, advise on agentic AI roadmaps, translate feedback to product teams, and create reusable templates. Expect regular customer interaction and up to 25% travel.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.