Staff Software Engineer

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

Do you have experience in TypeScript?, Do you have a Master's degree?, * 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

• 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.