Staff Product Engineer (m/f/d)

You get a business problem and you own it from there: solution concept, PRD, implementation, release, and measuring whether it worked. No hand-off, no shipping blind.

What you’ll do

• Get deep into the Sharpist product: the AI Coach, the coaching platform, the learner journey
• Audit existing solution concepts and PRDs; understand what's shipping and why
• Shadow one full problem-to-delivery cycle with the engineering team
• Ship your first small improvements or bug fixes First quarter:
• Own your first problem end-to-end: define the problem space, design the solution, write the PRD
• Use LLMs as a core workflow tool: prompt for specs, evaluate for efficiency and soundness, iterate
• Work directly with engineers to ensure what gets built matches what was intended
• Talk directly to users and stakeholders to ground each problem in real insight, not assumptions
• Give structured feedback on PRDs from others: technical feasibility, scope, edge cases Year one:
• Own multiple features end-to-end: define, ship, measure, and know what worked and what didn't
• Contribute to the team's weekly give & take: share what you learned, pick up what others discovered
• Make the developer experience meaningfully better: tooling, workflow, or process improvements the team actually uses

Requirements

Must-haves:

• You think like a Product Engineer: you've had full ownership of feature development, defining the solution, not just building what someone else specified
• You can write a clear, technically grounded PRD, and you know what makes one bad
• You have a strong intuition for UX: what confuses users, what creates friction, what feels right
• You use AI/LLM tools as a core part of how you work, across specs, prototyping, and implementation, not as a gimmick. Self-directed experiments and side projects count as evidence
• You can spot what LLMs miss: a wrong abstraction, a brittle data model, a spec that looks fine until it hits production
• Fluent English (written and spoken)

Nice to have:

• Experience building AI/LLM product features (prompting, evaluation, guardrails)
• Worked in a B2B SaaS or HR tech environment

We offer

You will join an engineering team that values a 'builder' culture, focusing on shipping, learning, and outcomes. We prioritize in-person collaboration to build strong relationships and foster the kind of conversations that evolve our product. The Engineering team consists of 5 people.

The Stack

TypeScript, React, React Native, Node.js, MongoDB, Redis, Docker, Google Cloud, BigQuery, Google Dataform, Lightdash, Prometheus, Grafana.