Full Stack Developer

Description

Reporting to the CTO, as a Full Stack Developer you will work across the full platform — a modular monolith built in .

NET 10 on the backend and React on the frontend.

You will own features from requirement to production, working in a small, high-trust team where your decisions have direct product impact.

Please submit your CV in English.

Requirements

• What You’ll Work On
• Backend (. NET / Modular Monolith)
• Build and extend modules within a clean modular monolith architecture — Domain, Application, Infrastructure, and API layers per module
• Implement message-based integrations over Rabbit MQ and HTTP, with proper retry, dead-letter, and observability patterns
• Design and own Postgre SQL schemas, migrations (Liquibase), and query optimisation for compliance-grade data integrity
• Write code test-first — unit tests, integration tests with in-memory and real DB where appropriate, and end-to-end API tests
• Contribute to and enforce coding standards, PR reviews, and architectural decisions.
• Frontend (React / Type Script)
• Build complex, accessible UI components and multi-path forms for compliance workflows
• Maintain consistency with our design system and work closely with our UX designer on new feature implementation
• Integrate with the backend via typed API contracts, handling loading states, error boundaries, and optimistic updates correctly
• AI-Augmented Development
• Use Claude Code as an active development tool — you will work with CLAUDE. md, SKILLS. md, and RULES. md context files to give the AI accurate codebase context
• Translate Jira requirements and Notion design documents into structured Claude Code prompts that produce high-quality, testable code
• Maintain and improve the Claude Code context layer as the codebase evolves, treating it as first-class documentation
• Evaluate AI-generated code with the same rigour as human-written code — you own the output
• Platform & Deployment
• Build and maintain Docker images for all services, following security and size best practices
• Deploy and manage workloads on Kubernetes clusters — writing and reviewing manifests, Helm charts, and managing config/secrets
• Collaborate with Dev Ops on CI/CD pipelines, environment configuration, and production readiness
• Participate in on-call rotation for production incidents (light, given our scale).
• What We’re Looking For
• Must-have
• 4+ years of professional . NET development (C#), with strong understanding of clean architecture and SOLID principles
• Solid React and Type Script experience — you write components that are readable, testable, and maintainable
• Genuine TDD discipline — you write tests before or alongside code, not as an afterthought; you understand the difference between unit, integration, and end-to-end tests
• Hands-on experience with Rabbit MQ or similar message brokers in production systems
• Postgre SQL proficiency — schema design, migrations, query analysis, and indexing
• Practical Kubernetes experience — you can read and write manifests, understand pod scheduling, and debug deployment issues
• Docker fluency — you build lean, layered images and understand multi-stage builds
• Experience working in or contributing to a modular monolith or DDD-influenced codebase
• Strong English communication skills — written and verbal
• Strong advantage
• Experience using Claude Code, Git Hub Copilot, or similar AI coding assistants as a genuine productivity tool in a professional codebase
• Familiarity with structuring AI context files (CLAUDE. md-style) to guide code generation effectively
• Experience with GCP (Cloud Run, Cloud Storage, Pub/Sub, Vertex AI)
• Playwright or similar e2e test framework experience
• Exposure to knowledge graphs, Neo4j, or graph-based data modelling
• Our Engineering Ethos

We are direct about what we expect. These are not aspirational values — they are how we work:

• Test coverage is a delivery requirement, not a nice-to-have. Core business logic ships with tests.
• PR reviews are substantive. We comment on architecture, not just typos.
• We use AI tooling to move faster, not to lower the quality bar. AI-generated code gets reviewed like any other code.
• We document decisions. ADRs, Notion pages, and Claude Code context files are part of the job.
• We raise issues early. A blocker surfaced on day one beats a missed deadline on day ten.