Top AI Engineer Jobs in San Francisco Bay Area, CA

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.

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.

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, 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 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 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.

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

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.

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.

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.

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.

As a Lead AI Engineer at Capital One, you will design and develop AI systems, collaborate with cross-functional teams, and optimize AI solutions for performance and scalability.