Senior Product Engineer; m​/w​/d

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.

You’ll take ownership of product features from problem to production. That means understanding the user and business need, exploring possible solutions, writing a clear technical specification, implementing the feature, releasing it, and learning from how people use it. You won’t simply receive finished tickets and build exactly what is written. You’ll be expected to ask good questions, identify edge cases, make pragmatic trade-offs, and help shape the right solution with Design and Engineering.

We’re working toward a one‑week cycle, although we’re not there yet. For now, we’d rather ship a useful first version at roughly 70%, learn from real usage, and improve it than spend too long polishing something in private. LLMs now handle a growing share of implementation. You should use them as part of your everyday workflow—for exploration, specifications, prototyping, and coding.

At the same time, you need the judgment to recognise when generated code, an abstraction, or a data model is wrong or likely to create problems in production.

• Learn the Sharpist product, including the AI Coach, coaching platform, and learner journey

• Understand our architecture, development workflow, and ways of working

• Pair with engineers and cross‑functional colleagues to understand how we take ideas into production

• Ship your first improvements to the product

• Own your first feature end‑to‑end: understand the problem, shape the solution, write the technical specification, build and release it

• Work closely with Product and Design to turn customer and user insight into a focused product experience

• Use LLMs as a core part of your workflow while validating their output for correctness, maintainability, security, and performance

• Contribute across the stack, including frontend, backend, data, testing, and deployment where needed

• Talk to users and stakeholders when direct context will help you make better decisions

• Own multiple product features from discovery through measurement and iteration

• Become a reliable technical owner for a meaningful part of the product

• Help improve engineering quality through better tests, observability, documentation, and development practices

• Contribute ideas that make it easier for the team to ship valuable software quickly and safely

Type Script, React, React Native, Node.js, MongoDB, Redis, Docker, Google Cloud, Big Query, Google Dataform, Lightdash, Prometheus, Grafana.
You don’t need experience with every technology listed. We care more about strong engineering fundamentals, the ability to learn quickly, and the judgment to choose appropriate solutions.

• 6+ 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 speak and write fluent English