Head of AI

Agentic workflows Agent architecture LLM orchestration Tool calling Agent memory RAG Customer-facing AI products Python ML systems architecture Machine learning Production AI systems Data engineering Enterprise AI Job Description Head of AI / Director of AI (title flexible) Location: San Mateo, CA (Bay Area) | Type: Full-time, permanent preferred | Experience: 5+ years About the Role You'll own the company's shift to becoming AI-native by leading the strategy, architecture, and delivery of agentic, customer-facing AI products that sit at the center of the business, not off to the side as internal tooling. This is the person who acts as the company's subject-matter expert on AI and agents, with ownership across the full product lifecycle, from ideation through shipping v1 and then iterating based on how customers actually use the product. The role is hands-on. You'll be expected to read and write production code, fix bugs, and get into the codebase. You'll directly lead a U.S.-based team of around five AI/ML engineers while working closely with a broader engineering organization in Bangalore, India. You'll also partner closely with product, GTM, and enterprise customers to understand real workflows and turn them into reusable agentic solutions that can serve customers across complex industries. This role is hybrid, based in San Mateo, CA, with at least Tuesdays and Thursdays in office and generally 2 to 3 days per week onsite. Responsibilities Own the AI systems architecture for customer-facing, agentic products Design, build, and scale agentic workflows that go well beyond simple LLM orchestration, with real command of agent components, tools, memory, and control flows Keep production AI systems reliable, performant, and maintainable Contribute code in Python and across the surrounding ML and engineering stack. Debug production issues, guide implementation details, and set engineering standards for the AI codebase. Lead and mentor a U.S.-based AI team of five or more engineers while collaborating with the broader engineering team in India Provide technical direction, code reviews, and career development support Help build a highly collaborative, in-office culture for the AI team, especially around triage, planning, and whiteboarding Partner with product and GTM on AI product strategy and roadmap Work directly with enterprise customers to understand their workflows and translate them into reusable agentic solutions Lead the team through v1 launches, then refine the product based on customer feedback and real usage data Define and track success metrics for AI features in production Qualifications Roughly 5+ years managing engineering or AI/ML teams, including the last 2 to 3 years directly managing a team that shipped and maintained a production AI product used by external customers, preferably in enterprise settings Strong Python and ML systems architecture experience You can personally contribute code and fix production issues. This is not a pure people-manager profile. Deep understanding of agentic systems, including how to design, implement, and own agents beyond simply calling third-party foundation models A track record of taking an AI/ML product from idea to GA launch to iterative improvement at a software or AI-native company, where AI was core to the product rather than a side project or internal optimization tool Preferred Familiarity with the data, data engineering, and analytics landscape Experience at software or AI-native companies making the move to agentic products Experience building AI for enterprise customers, especially in financial services, while working for a software or AI company rather than as an internal leader inside a bank Profiles to avoid Heads of AI inside large banks whose work is primarily internal, non-product, or focused on research or infrastructure Candidates whose AI work has been limited to internal tools, research, or proofs of concept, or whose work was not shipped to external users or central to the product's value Closing This is a role for someone who wants to own the AI that customers actually touch: setting the architecture, writing the code, leading a strong team, and shipping agents that are the product. If you've taken agentic products from idea to production for real enterprise customers and want to lead that work from the front, this is the seat. #J-18808-Ljbffr