Top AI Jobs in San Francisco Bay Area, CA

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.

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.

Lead and deliver large-scale AI/ML programs and the next-generation Generative AI platform. Build and grow a world-class TPM discipline, manage cross-functional delivery, mitigate technical risk, and drive execution across product, engineering, design, and data science to achieve business impact in regulated environments.

The AI Applications Engineer will prototype AI-driven solutions, collaborate with stakeholders, and create reusable components to address business challenges.

The AI Automation Senior Lead will build AI infrastructure, evaluate AI tools, redefine workflows, and maximize efficiency across teams at Taskrabbit.

As AI Enablement Services Lead, you will design AI solutions for operational tasks, automation of delivery processes, and enhance team capabilities in utilizing AI effectively.

Lead Gusto's AI/ML strategy, managing teams in Machine Learning Engineering, AI, and Risk Data Science. Ensure systems are reliable and impactful while fostering a culture of technical excellence.

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.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.

Lead a cross-organizational program to transition engineering to an AI-driven, self-optimizing ecosystem with robust telemetry and evaluation. Orchestrate strategy and execution, mitigate technical risk, build and grow a TPM practice, align product/engineering/design/data science, and deliver measurable business impact.

As an AI Engineer, you will develop and optimize AI systems for legal tasks, work on integrating models, and establish evaluation frameworks to enhance decision-making capabilities in complex legal workflows.

Lead design, launch, and lifecycle management of Pluralsight solutions (AI, Cloud, Security). Define expert POV, build curricula, labs, assessments, and blended learning programs. Own roadmap, metrics, GTM partnership with Sales and Marketing, and continuous iteration using data and SME collaboration to drive enterprise customer outcomes.

Lead and grow an AI Platform Enablement team to build a governed internal AI development environment. Define platform strategy, partner with security and infrastructure, drive adoption via enablement programs, and establish metrics for usage, onboarding, and control effectiveness. Act as an executive-facing leader delivering secure, scalable platforms and change management.

Lead product vision and strategy for an end-to-end AI-powered software factory. Integrate planning, coding, review, and verification across GitLab Duo Agent Platform and product areas. Collaborate with engineering, design, and GTM teams, identify gaps and dependencies, present recommendations to executives, and drive execution to deliver cohesive developer workflows.

As an AI Engineer, you will architect AI systems for legal work, lead technical initiatives, and mentor a team while impacting the future of legal technology.

Lead development of a 0→1 agentic AI finance product: define strategy, design solutions and UX, collaborate with engineering, design, and commercial teams, achieve product-market fit, and scale using cutting-edge LLM techniques.

The Machine Learning Scientist will develop AI frameworks for predictive modeling in oncology, collaborating with teams to enhance drug R&D efforts through advanced machine learning techniques and multimodal data integration.

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.