AI Product Operations Lead

New

TypeformForm software

For this role, we can hire candidates based in the UK, Ireland, Germany, Portugal or The NetherlandsFull-TimeLead

Salary not disclosed

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Job Details

Have strong practical experience applying AI to real-world problems and building solutions that people use.
Have a track record of taking ambiguous problems from discovery through implementation, testing, adoption, and ongoing improvement.
Apply systems thinking across people, processes, tools, data flows, integrations, permissions, and technical constraints.
Bring strong user and workflow discovery skills, including identifying the real job to be done and simplifying solutions.
Be comfortable building, modifying, and troubleshooting internal workflows, automations, agents, or applications.
Have practical experience with modern development practices and tools such as GitHub, repositories, and pull requests.
Understand basic application hosting, deployment, logging, and operational troubleshooting.
Manage work independently, including prioritizing a backlog, handling dependencies and risks, documenting decisions, and communicating with stakeholders.
Use evaluation and reliability practices to define success, test systems, collect feedback, and improve systems after launch.
Work effectively across technical and non-technical teams and make progress without close day-to-day direction.
Exercise good judgment around responsible AI, security, access, and governance, and know when to involve partners.

Build and improve a backlog of AI opportunities across R&D, helping teams identify, prioritize, and sequence work.
Take ambiguous problems from discovery through delivery, including understanding workflows, evaluating options, implementing solutions, testing, documenting, launching, measuring, and improving them.
Design AI-native solutions, choosing among prompts, workflows, integrations, agents, databases, and custom applications.
Help R&D get more value from Glean and Claude, partnering with IT and InfoSec on access, configuration, connectors, enablement, and support.
Own the lifecycle of portfolio AI systems, including automations, skills, agents, and internal web applications.
Establish practical approaches to evaluation, testing, reliability, observability, security, and maintenance.
Partner with R&D teams to uncover needs, unblock delivery, clarify ownership, and involve appropriate experts.
Evolve R&D AI governance and enablement practices, improving visibility into active work, risks, adoption, and outcomes.
Work with Finance and other partners to improve visibility into AI tool usage, spend, and value.
Explore and support autonomous agents for the product development lifecycle.

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