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Unmind is a mental health technology company that partners with enterprises (Uber, Disney, MLB, NHS) to improve employee mental health and organizational performance through science-backed digital solutions.
You'll join as a Full Stack Software Engineer, shipping end-to-end features that help enterprise clients' employees find the right mental health support. The role emphasizes ownership: you'll break down initiatives into deliverable slices, design solutions, write code, and shepherd features through testing, deployment, and production monitoring.
Key responsibilities:
- Ship features end-to-end with full ownership of design and implementation
- Choose pragmatic architectural approaches, write RFCs where needed, and make sensible trade-offs independently
- Maintain reliability: respond to incidents, improve observability, uphold security and performance standards
- Tackle tech debt, refactor, and upgrade dependencies to unblock delivery
- Embed AI into your development workflow using Claude Code for scoping, designing, coding, reviewing, and documenting; share learnings with the team
The team is actively exploring how to evolve development practices with AI assistance, making this a strong opportunity to deepen AI-assisted development skills in a supportive environment.
Unmind operates remote-first within the UK with monthly in-person meet-ups in London and access to a London co-working space. Benefits include private medical, equity, generous parental leave, 25 days holiday plus additional celebration days, monthly company-wide Fridays off, flexible working, annual learning budget, free weekly therapy/coaching, and wellbeing support.
REQUIREMENTS:
- Backend-leaning engineer comfortable moving across the full stack (TypeScript, React, GraphQL, Node.js, Python, Golang, SQL). Hands-on experience with every tool is not required; strong software engineering fundamentals and curiosity to learn are prioritized.
- Proven ability to ship impactful changes to customers regularly and solve problems from first principles
- Understanding of what it takes to build reliable products: performance, security, and observability built in from the start, not as follow-ups
- Code that is simple, well-tested, and easy for others to change
- Comfort with ambiguity and ability to find the leanest viable path forward
- Ability to make deliberate trade-offs, choosing lean over perfect when appropriate and being explicit about deferred work
- Comfort with AI-assisted development practices; experience using Claude Code or similar tools as a core part of feature development
- The company explicitly states education is not a factor in decision-making and invites candidates to remove education from CVs
