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Sharpist seeks a Staff Product Engineer to bridge product, design, and engineering. You own features end-to-end, define solutions, write specs, implement, release, and learn from usage.
You’ll work with AI and LLMs in everyday workflows while maintaining judgment to avoid production risks. You’ll collaborate across frontend, backend, data, testing, and deployment, ship a first useful version at ~70%, and iterate from real usage.
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.
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’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.
TypeScript, React, React Native, Node.js, MongoDB, Redis, Docker, Google Cloud, BigQuery, Google Dataform, Lightdash, Prometheus, Grafana.
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!