Backend Engineer ( TypeScript)

We help marketing teams unlock their growth potential with AI. Our attribution shows how advertising investments perform across channels and our optimizations shift budgets to where they drive the bottom line. Leading European brands in e-commerce telco banking insurance energy and more rely on us.

You build and run the services behind the Nexoya app: the GraphQL API ad channel integrations and data ingestion and new LLM- and agent-based features. You join a team of about 10 engineers across backend ML frontend and platform and you own your features from design to production.

AI coding agents change how software gets built but not who is responsible for it.

• Decisions are made together. Important technical decisions start as an Architecture Decision Record reviewed by the team. Good arguments win not seniority.

• Engineers design agents implement. Your design is the input for our coding agents guided by a shared rule set in our agent harness that the team evolves together.

• Working is not done. Code is ready when it is maintainable: readable tested robust on unhappy paths. Larger changes are reviewed so at least two engineers know every change.

• You build it you run it. A rotating internal support duty shows us which decisions worked.

• Ship backend features end to end on our Kubernetes-based Azure cloud.

• Evolve our GraphQL API with clear schemas and stable contracts.

• Build reliable ad channel integrations and data ingestion with MySQL and RabbitMQ.

• Build AI features such as our in-app assistant (tool calling retrieval structured outputs) with evaluation monitoring and guardrails.

• Help evolve our agent harness and raise the bar for tests reviews and documentation.

• 3 years as a Backend Engineer with and TypeScript.

• Solid API design (GraphQL or REST) and MySQL experience.

• Experience with message brokers and running services on Docker Kubernetes and a major cloud (Azure preferred).

• You enjoy discussing design trade-offs in writing and care about code others can maintain.

• Fluent English.

Bonus: ad platform APIs (Google Ads Meta) or attribution; AI or agent features in production (Anthropic/OpenAI APIs MCP RAG); LLM evaluation or observability; team use of Claude Code or similar; data pipelines; German.

• Direct impact on how enterprise marketers allocate their budgets.

• Real ownership in a team that takes engineering quality seriously.

• A genuine AI-first culture: experiment automate share.

• A transparent culture at eye level with regular team events.

• Strategy Days twice a year where the whole team shapes company strategy (past: Helsinki Berlin Belgrade Swiss Alps Zurich).

1. Profile review and phone screen

2. Take-home assignment: a backend feature

3. Technical discussion with the engineering team

4. On-site interview and team evaluation