Senior Product Manager, Coding

Handshake•San Francisco, CA

2d•$180,000 - $220,000•Hybrid

About The Position

Handshake AI powers expert-labeled data collection at scale, matching domain experts with leading AI companies to train frontier models. We're hiring a Senior Product Manager, Coding to own the roadmap for one of our frontier data modalities: coding. You'll define what we build, for whom, and on which surfaces as we learn what customers need from human data for training models to write, debug, and reason about code. This role is analogous to our RLE (Reinforcement Learning Environments) PM. You'll operate in high ambiguity—customers are still figuring out what "good" looks like, and the scope of coding as a data type is evolving. Your job is to navigate that ambiguity, narrow scope where it matters, and ship a coherent product that scales. You'll work closely with a cross-functional squad (engineering, design, operations) and with customer-facing teams to turn early signals into a repeatable offering. You'll own the coding modality end-to-end, including: Product strategy. Develop the product vision and roadmap for coding as a human data modality. Define the right scope (e.g., code review, debugging, generation, reasoning) and the right surfaces (platform capabilities, fellow training, quality bar) as we learn from customers. Customer discovery. Spend time with AI labs and internal stakeholders to understand how they use coding data, what standards they care about, and where our current offering falls short. Turn discovery into prioritized bets. Roadmap and scope. Make hard tradeoffs. We can't build everything; you'll decide what we build first and what we defer, and communicate that clearly to engineering, operations, and leadership. Cross-functional leadership. Lead a squad with engineering and design partners. Partner with Operator Experience, Fellow Experience, and other modality PMs—your scope enables and constrains theirs. Goals and metrics. Define success for the coding modality (e.g., capacity deployed, quality outcomes, time-to-staff). Track progress and hold the team accountable. Launch and iteration. Run pilots, gather feedback, and iterate. You'll be close to the first few projects and responsible for turning early wins into repeatable patterns.

Requirements

Software development experience.
Worked as a software developer at a tech company.
Operated on a small, early-stage team in a context where you were discovering customer problems, not just executing a known playbook.
Comfortable with ambiguity, shifting scope, and defining the problem as much as solving it.

Nice To Haves

FAANG or equivalent experience is strongly preferred.
5+ years in product, including time as a PM partnering with engineering to ship.
Experience in a frontier or emerging domain (new data type, new customer segment, 0→1) is a strong plus.
Technical credibility: can read and reason about code, review technical specs, and have informed opinions about code quality, review practices, and developer workflows.
Comfort with ambiguity: worked in environments where the problem wasn't fully defined.
Good at narrowing scope, saying no, and turning messy feedback into a clear direction.
Customer- and data-informed: use discovery and data to prioritize, but also make decisions when the signal is incomplete.
Action-oriented.
Systems thinker: see how the coding modality connects to platform, operations, fellow training, and quality.
Spot dependencies and edge cases and factor them into roadmap decisions.
Experience at a human data company, AI lab, or devtools company.
Prior role owning a frontier or net-new product area (0→1, new modality, or new segment).
Familiarity with AI/ML training data, annotation workflows, or code evaluation benchmarks.

Responsibilities

Develop the product vision and roadmap for coding as a human data modality.
Define the right scope (e.g., code review, debugging, generation, reasoning) and the right surfaces (platform capabilities, fellow training, quality bar) as we learn from customers.
Spend time with AI labs and internal stakeholders to understand how they use coding data, what standards they care about, and where our current offering falls short.
Turn discovery into prioritized bets.
Make hard tradeoffs, deciding what to build first and what to defer, and communicate that clearly to engineering, operations, and leadership.
Lead a squad with engineering and design partners.
Partner with Operator Experience, Fellow Experience, and other modality PMs.
Define success for the coding modality (e.g., capacity deployed, quality outcomes, time-to-staff).
Track progress and hold the team accountable.
Run pilots, gather feedback, and iterate.
Be close to the first few projects and responsible for turning early wins into repeatable patterns.