AI Product Operations Lead

Typeform is a form builder that helps over 150,000 businesses collect data through forms, surveys, and quizzes, driving 500 million responses annually. It integrates with tools like Slack, Zapier, and HubSpot.

About the Role

We are seeking an AI Product Operations Lead to build and operate the internal AI Operations capability for Research & Development (R&D).

This is a hands-on role for someone who can transform ambiguous opportunities into reliable, adopted solutions. You will:

• Identify the highest-value problems AI can solve across R&D.
• Understand workflows, design solutions, and ensure adoption and performance post-launch.
• Decide whether a simple prompt, automation, integration, agent, or internal app is the right solution.
• Improve existing AI workflows, test reliability, and coordinate access to enterprise AI tools.
• Collaborate with IT and InfoSec to ensure scalable, responsible solutions.

This role is not for someone who only wants to prototype prompts, manage project plans, or write requirements. Instead, it requires someone who enjoys combining systems thinking, AI fluency, user discovery, technical execution, and operational ownership.

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

Key Responsibilities

• Build and improve the backlog of AI opportunities across R&D, helping teams prioritize and sequence high-impact AI solutions.
• Take ambiguous problems from discovery to delivery, including understanding users, exploring options, designing systems, building or coordinating implementation, testing, documenting, launching, measuring, and improving.
• Design simple, AI-native solutions that fit naturally into workflows.
• Help R&D maximize value from enterprise AI tools like Glean and Claude, partnering with IT and InfoSec on access, configuration, connectors, enablement, and support.
• Own the lifecycle of AI systems, including automations, skills, agents, and internal web applications.
• Establish practical approaches to evaluation, testing, reliability, observability, security, and maintenance.
• Partner with teams across R&D to uncover needs, unblock delivery, clarify ownership, and bring in the right experts.
• Help run and evolve R&D AI governance and enablement practices, providing leaders with visibility into active work, risks, adoption, and outcomes.
• Participate in broader Typeform AI governance efforts.
• Collaborate with Finance to improve visibility into AI tool usage, spend, and value, informing investment decisions.
• Explore and support the development of autonomous agents to improve planning, discovery, design, building, evaluation, and management of work across the product development lifecycle.

Required Skills and Experience

• Strong practical experience applying AI to real-world problems, not just experimenting with models.
• A track record of taking ambiguous problems from discovery through implementation, testing, adoption, and ongoing improvement.
• Excellent systems thinking, understanding people, processes, tools, data flows, integrations, permissions, and technical constraints.
• Strong user and workflow discovery skills to understand real needs and simplify solutions.
• Hands-on technical fluency and comfort building, modifying, and troubleshooting internal workflows, automations, agents, or applications.
• Experience with modern development practices and tools such as GitHub, repositories, pull requests, deployment, logging, and troubleshooting.
• Experience managing work independently, including prioritizing backlogs, handling dependencies, documenting decisions, and communicating with stakeholders.
• A strong approach to evaluation and reliability, including defining success metrics, testing, collecting feedback, and improving systems post-launch.
• The ability to work effectively across technical and non-technical teams, asking questions, challenging assumptions, and seeking expert input.
• Good judgment around responsible AI, security, access, and governance, and an understanding of when to bring in the right partners.