Staff Software Engineer, Product (m/w/d)
Sharpist GmbH · Berlin, Berlin, Germany ·
- Work mode
- Hybrid
- Seniority
- Staff
- Category
- Software engineering
- Experience
- 10+ years
Sharpist GmbH · Berlin, Berlin, Germany ·
Sharpist exists to help people become more self-aware and effective at work and in life.
We combine human coaching with an AI Coach so that employees at every level can access meaningful support when they need it.
Our goal: to make coaching scalable – not to replace humans, but to enhance them.
As a Staff Product Engineer, you sit where that product meets the people using it. Your work turns that support into something people actually use to reflect, learn, and act.
🎥 Meet our AI Coach in action — and see how Sharpist empowers leaders and talents to grow every day:
You get a business problem and own it from there: shaping the solution, writing the technical specification, working through implementation, releasing it, and checking whether it actually worked. There is no hand-off in the middle and no shipping blind.
We’re working toward a one-week cycle, although we’re not there yet. For now, we’d rather ship at roughly 70%, learn from real usage, and improve the next version than spend too long polishing something in private.
The difficult part isn’t coding on its own. It’s the synthesis: taking a fuzzy problem and turning it into a technically sound, properly scoped solution quickly enough to keep the cycle moving. That’s where many engineers slow down. This role is here to close that gap.
LLMs now handle a growing share of implementation, and you should use them as part of your everyday workflow. What they can’t replace is the judgment to recognise when the architecture is wrong, when an abstraction won’t hold, or when a shortcut is likely to become next quarter’s incident. The important thing is catching that before it gets built, rather than after it reaches production.
First 30 days:
Get deep into the Sharpist product: the AI Coach, the coaching platform, and the learner journey
Audit existing solution concepts and technical specifications so you understand what’s shipping and why
Shadow a full problem-to-delivery cycle with the engineering team
Ship your first improvements to the product
First quarter:
Own your first problem end-to-end: define the problem space, design the solution, and write the technical specification
Use LLMs as a core workflow tool: prompt for specifications, evaluate the results for efficiency and soundness, and iterate
Work directly with engineers to make sure what gets built matches what was intended
Talk directly to users and stakeholders, grounding each problem in real insight rather than assumptions
Give structured feedback on technical specifications from others, especially around technical feasibility, scope, and edge cases
Year one:
Own multiple features end-to-end: define them, ship them, measure them, and understand what worked and what didn’t
Contribute to the team’s weekly give & take by sharing what you learned and picking up what others discovered
Make the developer experience meaningfully better through tooling, workflow, or process improvements the team actually uses
TypeScript, React, React Native, , MongoDB, Redis, Docker, Google Cloud, BigQuery, Google Dataform, Lightdash, Prometheus, Grafana.
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.
Must-haves:
10+ years of professional software engineering experience.
You think like a Product Engineer: you’ve owned full feature development, including defining the solution rather than only building what someone else specified
You can write a clear, technically grounded specification, and you know what makes one bad
You have strong intuition for UX: you notice what confuses users, what creates friction, and what feels right
You use AI and LLM tools as a core part of how you work across specifications, 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, or a specification that looks fine until it meets production
You speak and write fluent English
You have valid work permit in Germany
Nice to have:
Experience building AI or LLM product features, including prompting, evaluation, or guardrails
Experience working in a B2B SaaS or HR tech environment
Ownership: When ownership is unclear, you step forward. When you're blocked, you find a solution; you don't shift the problem up
Clarity: You write specs that don't need a meeting to explain
Judgment: You know when something is technically sound vs. technically plausible-but-painful
Speed: You move fast without creating rework for others
Mission belief: You genuinely care about helping people. That's why you're here
Unlimited Coaching: Access certified coaches to support your personal and professional growth whenever you need it.
Hybrid working model : Enjoy the flexibility to work both remotely and on-site.
Growth Budget: 1000 EUR per year dedicated budget for courses, workshops, and certifications.
Pension Scheme (bAV): Attractive retirement savings program.
Quarterly Magnetic Week : Connect with your colleagues at exciting events that inspire and excite.
The "Builder" Environment: A culture that values shipping, learning, and outcome over output.
💙 We are an equal opportunity employer and we encourage people of every ethnic background, gender, ability, and sexual orientation to apply. 🙂
✨ Curious what life at Sharpist looks like? Check out here - from Tuesday BBQs to Thursday breakfast, it's all part of what makes our team so special!
Apply now if this captures your interest and you want to take part in the personalisation of learning for every employee worldwide. We are excited to get to know you!