AI Product Operations Lead

We're looking for an AI Product Operations Lead to build and operate the internal AI Operations capability for R&D.

This is a hands-on role for someone who can take an ambiguous opportunity and turn it into a reliable, adopted solution. You'll help us identify the highest-value problems AI can solve, understand how people work today, design the right solution, build or coordinate its delivery, and then stay accountable for how it performs after launch.

• Build and continuously improve our backlog of AI opportunities across R&D, helping teams identify, prioritize, and sequence the jobs where AI can have the greatest impact.
• Take ambiguous problems from initial discovery through to delivery: understand the user and workflow, explore options and trade-offs, design the right system, build or coordinate implementation, test, document, launch, measure, and improve.
• Design simple, AI-native solutions that fit naturally into how people work. You'll know when a prompt is enough—and when the problem calls for a workflow, integration, agent, database, or custom application.
• Help R&D get more value from enterprise AI tools such as Glean and Claude, partnering with IT and InfoSec on areas including access, configuration, connectors, enablement, and support.
• Own the lifecycle of the AI systems within your portfolio, including automations, skills, agents, and internal web applications.
• Establish practical approaches to evaluation, testing, reliability, observability, security, and maintenance—using evidence and feedback to improve systems over time.
• Partner with teams across R&D to uncover needs, unblock delivery, clarify ownership, and bring the right experts into the work.
• Help run and evolve our R&D AI governance and enablement practices, giving leaders better visibility into active work, risks, adoption, and outcomes.
• Participate in Typeform's broader AI governance efforts as an R&D contributor.
• Work with Finance and other partners to improve visibility into AI tool usage, spend, and value, helping inform investment decisions.
• Explore and support the development of autonomous agents that can improve how we plan, discover, design, build, evaluate, and manage work across the product development lifecycle.

• Strong practical experience applying AI to real-world problems—not just experimenting with models, but building solutions that people actually use.
• A track record of taking ambiguous problems from discovery through implementation, testing, adoption, and ongoing improvement.
• Excellent systems thinking. You can understand how people, processes, tools, data flows, integrations, permissions, and technical constraints fit together—and make thoughtful trade-offs between different approaches.
• Strong user and workflow discovery skills. You know how to get beyond the initial request, understand the real job to be done, and simplify a solution when the original approach is more complex than it needs to be.
• Hands-on technical fluency and comfort building, modifying, and troubleshooting internal workflows, automations, agents, or applications.
• Practical experience with modern development practices and tools such as GitHub, repositories and pull requests, basic application hosting, deployment, logging, and operational troubleshooting.
• Experience managing work independently: prioritizing a backlog, handling dependencies and risks, documenting decisions, and communicating clearly with stakeholders.
• A strong approach to evaluation and reliability. You think about what "good" looks like, how to test for it, how to collect feedback, and how to improve a system after it goes live.
• The ability to work effectively across technical and non-technical teams. You're comfortable asking questions, challenging assumptions, seeking expert input, and making progress without needing close day-to-day direction.
• Good judgment around responsible AI, security, access, and governance, and an understanding of when to bring in the right partners.