AI Product Operations Lead

About the Team

Product Operations sits at the center of how our Product and wider R&D teams work. We help create the systems, practices, and connections that allow teams to focus on solving the right problems and delivering great products.

AI is becoming an increasingly important part of that work. Across R&D, teams are already experimenting with tools like Glean and Claude, building automations, testing agents, and finding new ways to use AI throughout the product development lifecycle.

The opportunity now is to turn that energy into something more systematic. That’s where you come in.

About the Role

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 enjoys figuring things out for themselves. We’re hiring our first dedicated AI Product Operations Lead – you’ll work as an individual contributor and be expected to take ownership of problems end to end, from first conversation through to adoption.

One day, you might be exploring a workflow with a Product team to understand where AI could help. The next, you might be building an automation, configuring an enterprise agent, creating a new Claude skill, improving logging and evaluation, or helping a team improve how they’re using Glean.

You’ll own the connective layer between an opportunity and a solution that actually gets adopted: the discovery, workflow design, technical implementation, change management, evaluation, reliability, ownership, governance, and continuous improvement required to make AI useful and sustainable at scale.

This isn’t a role for someone who only wants to prototype prompts, manage project plans, or write requirements. We’re looking for someone who enjoys combining systems thinking, AI fluency, user discovery, technical execution, and operational ownership—and who wants to see things through.

You’ll report to our VP of Product Operations and work closely with Product, Engineering, Design, Research, Data Science, IT, InfoSec, and other AI practitioners across Typeform.

What You’ll Do

• Build and continuously improve our backlog of AI opportunities across R&D, helping teams identify, prioritize, and shape problems where AI can have the most impact.
• Take ambiguous problems from initial discovery through to delivery: understand the user and workflow, uncover constraints, map processes, identify risks, and design solutions that people can actually use.
• 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 applications, from opportunity sizing and success measures through to launch, adoption, and ongoing improvement.
• Establish practical approaches to evaluation, testing, reliability, observability, security, and maintenance for AI solutions, and make sure the right ownership, support, and escalation paths are in place.
• Partner with teams across R&D to uncover needs, unblock delivery, clarify ownership, and bring the right expertise into the room, including Product Operations peers such as Voice of the Customer, Product Intelligence, Product Process, Release, Tooling, and Product Experience.
• Help run and evolve our R&D AI governance and enablement practices, giving leaders better visibility into which opportunities are progressing, where support is needed, and where investment is having the greatest impact.
• 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 future investment decisions.
• Explore and support the development of autonomous agents that can improve how we plan, discover, design, develop, and ship products.

What You’ll Bring

• 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…