What You Will Do
- Own and scale a new area of our AI-native suite, from early product to broad adoption.
- Design systems, not features β the full loop from data capture to AI synthesis to workflows like reviews and calibration.
- Define what good AI looks like in a trust-critical product: transparent, evidence-backed, user in control.
- Partner deeply with Reviews, Grow, and Calibration so this becomes core to Lattice.
- Lead through ambiguity and own the hardest product questions.
What You Will Bring
- 7 to 12+ years building complex, data-rich, or workflow-heavy products.
- A builder mindset: youβre comfortable prototyping, working in design tools, and using modern AI tools (e.g., Claude, Cursor, coding agents) to accelerate how you work.
- A strong bias toward execution and iteration - you value getting real products in front of users and learning quickly.
- Excellent prioritization skills; you can identify the highest-leverage opportunities and focus teams accordingly.
- High agency, ownership and initiative - you proactively identify what matters most and move it forward.
- Experience building 0β1 product, ideally in fast-moving AI-first environments and demonstrating real impact.
- Bonus points if the product was AI-native from day one β where latency, evals, prompts, and model selection were daily concerns, not abstractions.
- Experience taking products beyond launch and driving meaningful and measurable scaled adoption.
- Strong customer obsession. You stay close to customers and their needs shape your decisions.
- Strong product judgment. You have a clear perspective on quality, trust, and user experience, and can defend it.
- AI/ML experience (especially LLMs), both in products you've shipped and in the tools you use to do your own job, plus judgment about when not to use AI.
- GM-style collaboration across eng, design, data, legal, and GTM. You make the people around you better.
- Comfort with data. You can write your own SQL, read a dashboard, and pressure-test a metric without waiting for an analyst.
Very-Nice-to-haves
- Founder Experience or very early stage start-up experience, moving through ambiguity to make progress.
- HR tech, performance management, or internal tooling experience.
- Background in developer tools or structured data ecosystems.
