Product Operations Lead, Generative AI

You will:

• 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 Scale’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

Ideally, you'd have:

• 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