AI Product Operations Lead

Overview

As AI Product Operations Lead, you will build and run the internal AI operations for R&D, turning ambiguous AI opportunities into reliable, adopted solutions. You’ll coordinate discovery, design, delivery, and ongoing optimization of AI-enabled workflows, agents, and integrations. You’ll work across Product, Engineering, IT, and InfoSec to scale responsible AI and improve how teams plan, discover, and build with AI. This role combines systems thinking with practical AI delivery to maximize impact across Typeform’s R&D portfolio.

Responsibilities

• Build and optimize the AI opportunity backlog across R&D
• Translate discovery into delivery, including design, implementation, testing, launch, and iteration
• Design AI-native solutions aligned with how people work (prompts, workflows, integrations, agents, databases, apps)
• Enable value from enterprise AI tools (Glean, Claude) with IT/InfoSec collaboration on access and connectors
• Own lifecycle of AI systems (automations, skills, agents, internal apps)
• Establish evaluation, reliability, observability, security, and maintenance practices
• Collaborate across R&D to clarify ownership, unblock delivery, and bring in needed experts
• Evolve R&D AI governance and enablement practices for visibility on risk, adoption, and outcomes
• Coordinate with Finance on AI tool usage, spend, and value to inform investments
• Explore autonomous agents to improve planning, discovery, design, build, and management of work across the lifecycle

Key requirements

• Practical AI deployment experience—beyond experimentation
• Track record delivering ambiguous problems from discovery to adoption
• Strong systems thinking across people, processes, tools, data, and constraints
• User and workflow discovery skills with simplification ability
• Hands-on technical fluency to build or modify internal workflows, automations, agents, or apps
• Experience with modern development practices (GitHub, PRs, hosting, deployment, logging)
• Independent work style: backlog management, dependency handling, risk awareness, clear communication
• Evaluation and reliability mindset: testing, feedback-driven improvements
• Ability to collaborate across technical and non-technical teams
• Judgment on responsible AI, security, access, and governance

• cross-functional collaboration
• problem framing
• clear communication
• AI workflow design
• automation and agent development
• internal app development and hosting

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