Senior Golang Engineer (AI Platform)

About the Role

We are looking for an experienced Senior Golang Engineer to help us build and scale our AI platform.

This role is highly product-oriented, with a strong focus on rapid iteration, experimentation, and delivering production-ready AI functionality. You will work primarily on building backend services, APIs, and platform capabilities that power AI workflows and tools, while collaborating closely on user-facing applications where needed.

The ideal candidate combines strong backend engineering in Go, solid software architecture skills, and practical experience working with AI systems and LLM-based applications. Frontend experience with React and TypeScript is a plus, but not the core focus of the role.

We are looking for someone who can take ownership of technical initiatives, contribute architectural ideas, and drive projects from concept to production and beyond, while balancing innovation with operational pragmatism.

Your Responsibilities

• Design, build, and operate scalable and reliable backend services and platform components in Go.

• Build APIs and integrations between internal services, AI models, and external systems.

• Develop AI-powered workflows, including agent-based solutions where they provide clear product value.

• Contribute to the architecture of AI solutions and drive their implementation together with the engineering team.

• Design systems with clear failure modes, fallbacks, and strong debuggability.

• Consider evaluation, observability, latency, reliability, and cost when productionising LLM-based functionality.

• Monitor and improve the quality and operational performance of AI-powered features.

• Lead technical initiatives from concept through implementation, deployment, and production operation.

• Write maintainable, well-tested, and idiomatic Go code.

• Participate actively in code reviews and architectural discussions.

• Collaborate closely with Product, QA, and other engineers to deliver functionality in short feedback loops.

• Evaluate emerging AI technologies pragmatically and introduce them when they provide measurable value.

• Support the development of user-facing applications when needed, in collaboration with the wider team.

Requirements

• 5+ years of commercial experience in software engineering.

• Strong backend development experience with Go.

• Experience developing backend or platform systems in production environments.

• Solid understanding of software architecture and system design.

• Experience building systems with high scalability, availability, and reliability requirements.

• Hands-on experience with observability tools and practices (metrics, logs, tracing, alerting).

• Experience working with Docker, Git, and CI/CD pipelines.

• Practical experience with AI tools, LLM APIs, or AI-driven workflows.

• Ability to effectively use modern AI development tools such as Cursor or Claude.

• Proven ability to lead technical initiatives from concept to production.

• Strong communication skills and ability to work effectively in a collaborative environment.

• High level of ownership and proactive mindset.

• Fluent English (minimum B2).

Nice to Have

• Experience building AI agents or agent-based workflows.

• Experience with RAG architectures, vector databases, or LLM integration pipelines.

• Experience evaluating and monitoring LLM-based functionality in production.

• Experience with prompt and model versioning, fallback strategies, or multi-model solutions.

• Experience building frontend applications with React and TypeScript.

• Experience developing full-stack applications in production environments.

• Experience with RabbitMQ or other messaging technologies.

• Experience designing automated testing strategies for distributed systems.

• Knowledge of German.

Our Tech & QA Stack

• Languages/Frameworks: Go, JS/TypeScript, PHP

• Databases: MySQL, MariaDB

• Infrastructure: UNIX, Kubernetes, RabbitMQ

• Testing: Playwright, Python, Dart, Postman

• CI/CD: GitLab CI, Code Magic

• Containerization: Docker

• AI Tools: JetBrains AI, Cursor, Gemini, Claude

• Tools: Jira, Requirements & Test Management for Jira, Confluence, Slack, IDE (freedom of choice), G-Suite, Sentry

Engineering Culture

• Product-oriented engineering with short feedback loops.

• Pragmatic architecture and idiomatic Go.

• End-to-end ownership from design through production operation.

• Automated testing, code reviews, observability, and operational readiness.

• AI-assisted development with human validation and engineering accountability.

• Continuous experimentation combined with measurable product value.

Benefits and Perks

• Private healthcare

• Cafeteria system

• Training budget €800 per year

• Integration meetings (internal training, hackathon, integration trips, and meetings)

• Referral Bonus

• Startup atmosphere

• No dress code

• Flexible hours

• Flexible working format - remote or hybrid

• Modern office, Chillout zone, Standing desk, parking for bicycles, and a cloakroom with showers

• Regular office lunches and integration meetings

• Some international travels included