Senior Software Engineer (m/w/d)
Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Oct 8, 2026.
At Pflegia we build and operate an intelligent job matching platform that brings caregivers and healthcare employers together. Our vision is to become Europe's leading job platform for nursing professions and to fight the nursing crisis.
Our platform runs in production every day: a TypeScript monorepo, a matching engine, our own data lake and an end-to-end suite that runs on every pull request. AI coding agents are part of how we build it. We are looking for a senior engineer who uses them to ship more, and who knows exactly where their output must not be trusted. Become part of the team and shape the nursing job market with us.
Tasks
Take full ownership of features from concept to production, across frontend, backend, data and infrastructure, in short iteration cycles.
Work with AI coding agents every day: break work into steps an agent can execute, give it the context and constraints it needs, and review its output as critically as a colleague's pull request.
Build the guardrails that make AI-assisted development safe at speed: types, tests, lint rules, CI checks and review conventions that catch what an agent gets wrong before a user does.
Keep the codebase legible for humans and agents alike: clear module boundaries, documented conventions, small focused changes.
Architect scalable, secure and maintainable software and infrastructure, and shorten the path from merged pull request to production, which today is measured in days rather than hours.
Instrument what you ship. Every behaviour-changing release comes with the metric that tells us whether it worked. Within 90 days we expect one improvement you shipped and measured, with a baseline, a number and a read you can defend.
Conduct code reviews and mentor colleagues, including on how to work effectively with AI tools, raising the whole team to the next level.
Collaborate with product, QA and the data team, and communicate trade-offs, progress and risks clearly to stakeholders.
Requirements
Must have
5+ years of professional software development, with production full-stack TypeScript experience.
Great TypeScript and SQL skills. Our stack: React, react-admin, Next.js, NestJS, GraphQL (Apollo), TypeORM and PostgreSQL in an Nx monorepo.
Hands-on experience shipping production code with AI coding agents (we use Claude Code; Cursor, GitHub Copilot or similar count too). In the interview you can show how you give an agent context, how you verify its work, and when you throw the output away.
Testing as a habit, not a phase: unit and integration tests (Jest, Vitest or similar) and a working understanding of end-to-end testing (we use Playwright). With agents writing code, tests are the specification.
Very good knowledge of security best practices, including the risks AI tooling adds: secrets and personal data in prompts, hallucinated or unvetted dependencies, plausible-looking but wrong code.
Cloud and delivery experience with AWS and Vercel, CI/CD with GitHub Actions.
Agile and Scrum working practices, good time management and organizational skills.
Excellent verbal and written communication and conceptualization skills in English (German is a plus).
Nice to have
Building with LLMs inside the product, not only in the editor: prompt design, evaluation, cost and latency trade-offs.
Agent tooling beyond autocomplete: custom instructions, skills, MCP servers, or automations that let agents run tests, read logs and open pull requests.
Data engineering (ETL) and data analytics. Our data lake runs on AWS Athena, and the engineers who enjoy this role usually query it themselves.
Observability with Datadog or similar: logs, RUM and metrics you actually look at after a release.
Matching or recommendation systems, or two-sided marketplaces.
Benefits
Real ownership. Flat hierarchies with short decision paths: you will not need a committee to ship.
AI coding tools provided and expected, with room to shape how the team uses them.
Direct access to the data: our own data lake, dashboards and product analytics, so you can check the effect of your own work.
Budget and room for experiments that are allowed to fail, provided the expected outcome was defined up front.
Regular feedback conversations with empathic and experienced leadership.
An open corporate culture with helpful, communicative colleagues and a genuinely cooperative working atmosphere.
Central Berlin office in a beautiful old building, plus flexible remote.