About Sharpist

At Sharpist, our mission is clear: to empower everyone to lead a self‑aware career and life.

We make coaching accessible for all – anytime, anywhere.

We’re building a hybrid coaching experience: genuine 1:1 coaching for empathy and accountability, combined with an AI Coach for quick insights, follow‑ups, and in‑the‑moment support.

Our goal: to make coaching scalable – not to replace humans, but to enhance them. Human and intelligent.

Meet our AI Coach in action — and see how Sharpist empowers leaders and talents to grow every day:

The Role

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. We're working toward a one-week cycle, but we're not there yet. We'd rather ship at ~70% and learn from real usage than polish in private.

The hard part isn't the coding. It's the synthesis: going from a fuzzy problem to a technically sound, scoped solution fast enough to keep the cycle moving. That's where most engineers slow down. That's the gap this role fills.

LLMs handle a growing share of the implementation. What they can't replace is the judgment to know when the architecture is wrong, when an abstraction won't hold, when a shortcut becomes next quarter's incident. Catching that before it's built, not after.

What you’ll do

First 30 days:

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

The Stack

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

Working Model

Hybrid in Berlin, 3 days per week in the office. We find that being together in person is what builds the kind of relationships where real conversations happen: the ones that change how you think, how you work, and how the product evolves.

Who You Are

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

What We Value

Ownership: When ownership is unclear, you step forward. When you're blocked, you find a solution; y

Staff Software Engineer (m/w/d)

Description