Summary
What you’ll impact
The Product Operations Manager at our organization’s Generative AI business will bridge Operations and Product, shaping roadmaps and modernizing tooling. They will lead high‑priority, operations‑intensive initiatives, partner with Product and Engineering to define metrics, and use data analytics to drive impact.
Responsibilities
What you'll do
- Own the connection between Operations and Product. Surfacing the needs of operators across the GenAI business, building the case for what should be built next, and shaping a product roadmap grounded in the reality of running frontier data projects
- Modernize operations tooling with agents. Identify which processes should be managed by agents, partner with engineering to connect tools, hillclimb the agents through evals, and redesign the workflows around them
- Drive our highest‑priority, operations‑intensive initiatives end to end, from planning through execution and adoption across the organization
- Partner with Product and Engineering leads to define success metrics, track how initiatives are performing, and make data‑driven decisions
- Be the voice of the operator across the organization’s Product and Engineering teams. Provide operator context, early feedback on features, and connect with the right stakeholders to build successful products
- Leverage data analytics tools (SQL, Python, coding agents) to quantify the impact of operational problems, inform prioritization, and measure whether what we ship actually works
Requirements
What you’ll bring
- 4+ years of experience in Product Operations, Technical Program Management, Strategy & Operations, or delivery operations within high-growth tech environments; the ideal candidate will have 6+ months of experience delivering GenAI data pipelines
- A strong product sense and ability to prioritize the highest leverage initiatives
- A cross-functional operator: proven ability to understand a customer's underlying need, separate it from the stated request, and influence Product, Engineering, and Ops partners without direct authority
- Familiarity with the GenAI data business: how projects are staffed, run, and delivered, and where operators feel friction day to day
- Strong technical background (a degree in computer science or STEM is ideal, and at minimum, the role requires the ability to perform independent data analytics using SQL or Python)
- Proven ability to communicate complex technical concepts to non-technical stakeholders and translate operational "friction" into engineering solutions
- An entrepreneurial and high-ownership mindset: you are comfortable building 0-to-1 processes, handling ambiguity, and driving workstreams from conception to execution
- Bias for lightweight structure and doing: you build well designed processes people actually use and know when not to add more