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Salary: USD 180,800 - 226,000 / annual
Scale's Generative AI business unit is seeking a Product Operations Manager to build and support critical processes and platforms driving daily operations. This role bridges product, operations, and analytics, requiring the ability to translate complex requirements between technical teams and operational stakeholders.
Key Responsibilities:
- Own the connection between Operations and Product, surfacing operator needs across the GenAI business and shaping a product roadmap grounded in the reality of running frontier data projects
- Modernize operations tooling with AI agents: identify which processes should be managed by agents, partner with engineering to connect tools, evaluate agent performance, and redesign workflows accordingly
- Drive highest-priority, operations-intensive initiatives end-to-end, from planning through execution and organizational adoption
- Partner with Product and Engineering leads to define success metrics, track initiative performance, and make data-driven decisions
- Serve as the voice of the operator across Scale's Product and Engineering teams, providing operator context, early feature feedback, and connecting stakeholders
- Leverage data analytics tools (SQL, Python, coding agents) to quantify operational problems, inform prioritization, and measure impact of shipped solutions
The ideal candidate will translate complex requirements between technical and operational teams, earn trust from both sides, and influence direction without direct authority. You'll handle ambiguity, build 0-to-1 processes, and drive workstreams from conception to execution.
Requirements:
- 4+ years of experience in Product Operations, Technical Program Management, Strategy & Operations, or delivery operations within high-growth tech environments; 6+ months of experience delivering GenAI data pipelines is ideal
- Strong product sense and ability to prioritize high-leverage initiatives
- Proven cross-functional operator: ability to understand underlying customer needs, separate from stated requests, and influence Product, Engineering, and Ops partners without direct authority
- Familiarity with the GenAI data business: how projects are staffed, run, delivered, and where operators experience friction
- Strong technical background (computer science or STEM degree ideal; minimum requirement is 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
- Entrepreneurial, high-ownership mindset; comfortable with ambiguity and driving workstreams from conception to execution
- Bias for lightweight structure and doing: build well-designed processes people actually use and know when not to add more
