Product Operations Manager - AI

Rec Technologies•San Francisco, CA

2d•$150,000 - $180,000•Onsite

About The Position

Rec is using AI to reimagine how the world plays, participates in community, and gets active. Our vision is simple: more recreation for everyone. We sit at a rare intersection — a consumer product loved by everyday players and an enterprise platform trusted by the organizations that power recreation. We're a small team with firepower. Our founders were among the first few hundred at Uber, then led teams at The Athletic and MasterClass. The rest of the team combines builders from Google, Microsoft, Strava, Hipcamp, and Airbnb. People join Rec for two reasons: you want to build AI that gets people back in the real world, and you want to work with really smart people. Seb, Rec's AI agent, only gets better if someone is relentlessly closing the loop between how it performs in the real world and how it improves. As our Product Operations Manager - AI, you're that person. You'll run the quality engine behind Seb — evals, annotation, defect triage — and you'll be the connective tissue that keeps AI initiatives moving across product, engineering, and the business. You care as much about the annotation queue as you do about whether a launch actually shipped on time. Some days you're deep in eval results deciding whether a regression is a defect or a preference issue. Other days you're making sure five different workstreams converge on the same launch date.

Requirements

5+ years in product operations, program management, or a related operational role — ideally with exposure to AI/ML products.
Comfortable getting hands-on with evals, annotation tools, and quality frameworks, even without a formal ML background.
Highly organized — you can run multiple workstreams at once without losing the thread.
A clear communicator who can translate messy technical detail into a simple status update or decision
Genuinely curious about AI and how agents actually behave in production
Comfortable in ambiguity — you build the process where none exists yet.
Bias toward action and high attention to detail in equal measure.

Responsibilities

Run Seb's evaluation and quality operations — building and maintaining eval sets, managing annotation queues, and classifying issues as defects vs. preferences.
Own the feedback loop between real-world agent performance and the roadmap — turning quality signals into clear, prioritized fixes.
Drive cross-functional AI program management — keeping roadmaps, launches, and dependencies across product, engineering, and design on track.
Build and refine the operational infrastructure (observability, scoring, review workflows) that lets the team trust Seb's quality at scale.
Partner with engineering on the practical realities of shipping AI features — instrumentation, monitoring, and rollout sequencing.
Spot patterns across evals and staff feedback that point to bigger product or trust issues before they become customer-facing problems.
Keep AI leadership and stakeholders clearly informed on program status, quality trends, and risk.