AI Product Operations Lead
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Job Description
AI Product Operations Lead building and operating internal AI capabilities for Typeform’s form-building platform. Improving R&D workflows, governance, reliability, and enterprise AI adoption.
Responsibilities:
- Build and continuously improve the backlog of AI opportunities across R&D
- Take ambiguous problems from discovery through delivery, testing, documentation, launch, measurement, and improvement
- Design simple, AI-native solutions using prompts, workflows, integrations, agents, databases, or custom applications
- Help R&D use enterprise AI tools such as Glean and Claude, partnering with IT and InfoSec on access, configuration, connectors, enablement, and support
- Own the lifecycle of automations, skills, agents, and internal web applications
- Establish approaches to evaluation, testing, reliability, observability, security, and maintenance
- Partner across R&D to uncover needs, unblock delivery, clarify ownership, and involve experts
- Help evolve R&D AI governance and enablement practices
- Participate in Typeform’s broader AI governance efforts
- Work with Finance to improve visibility into AI tool usage, spend, and value
- Explore and support autonomous agents across the product development lifecycle
Requirements:
- Strong practical experience applying AI to real-world problems and building solutions that people use
- Track record taking ambiguous problems from discovery through implementation, testing, adoption, and ongoing improvement
- Excellent systems thinking across people, processes, tools, data flows, integrations, permissions, and technical constraints
- Strong user and workflow discovery skills
- Hands-on technical fluency building, modifying, and troubleshooting internal workflows, automations, agents, or applications
- Practical experience with GitHub, repositories and pull requests, basic application hosting, deployment, logging, and operational troubleshooting
- Experience managing work independently, including backlogs, dependencies, risks, documentation, and stakeholder communication
- Strong approach to evaluation and reliability, including testing, feedback collection, and post-launch improvement
- Ability to work across technical and non-technical teams without close day-to-day direction
- Good judgment around responsible AI, security, access, and governance
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