Senior Backend Engineer - Python

You'll be responsible for the technical backbone of our product-shaping architecture decisions, evolving production systems, and setting the engineering standard as our team grows:

• Define and evolve our backend architecture-making strategic decisions on service boundaries, data flows, and scaling patterns.
• Design and build high-throughput content ingestion and transformation pipelines that reliably process thousands of articles daily.
• Own the full lifecycle of our core API services (FastAPI)-from design through deployment to operational excellence.
• Establish backend engineering standards: code quality, testing strategies, documentation practices, and review processes.
• Drive infrastructure decisions-evaluate trade-offs between cloud services, optimize costs, and ensure our systems are observable and resilient.
• Mentor and guide future engineering hires as the team scales., How we define success:
• You've established architectural patterns and engineering practices that the team builds on confidently.
• The systems you own run reliably in production with clear observability-issues are caught before users notice.
• Your technical judgment earns trust across the team, and your decisions hold up as we scale.
• Editors and internal users experience a noticeably more stable, faster product.

Why us?

• Shape the technical foundation of a product used by major German publishers.
• Be the senior engineering voice in a small, high-impact team with direct influence on product and architecture.
• Support trustworthy journalism in the age of AI.
• Berlin-based hybrid setup with genuine home office flexibility.
• Early-stage equity opportunity-your work directly drives company value.

• 5+ years of professional Python development, with significant experience designing and operating production backend systems
• Deep knowledge of async frameworks (FastAPI or equivalent) and RESTful API design
• Strong data modeling skills-MongoDB or other document/NoSQL databases at scale
• Solid understanding of distributed systems patterns: queues, event-driven architectures, idempotency, graceful degradation

AI & Platform:

• Hands-on experience integrating and orchestrating LLM APIs (OpenAI, Anthropic, or similar) in production
• Familiarity with LangSmith, LangChain, or comparable orchestration/observability tooling
• Ability to reason about prompt engineering trade-offs, token economics, and model selection
• Up to date and clear on pros and cons of agent-assisted software developement

DevOps & Infrastructure:

• Production AWS experience (ECS, Lambda, S3, SQS, or similar services)
• Docker, CI/CD pipelines (GitHub Actions), infrastructure-as-code
• Hands-on with monitoring, logging, and alerting-you've been on-call and know what matters when things break

How You Work:

• You think in systems, not just features-anticipating failure modes and scaling bottlenecks before they hit
• You make pragmatic trade-offs between moving fast and building for durability
• You communicate technical decisions clearly, both in writing and in conversation
• You've operated in environments where you had to define process, not just follow it
• You love to deploy as often as you can and to test in production

Experience in early-stage or high-growth startups is a strong plus. You excel at taking ownership, handling ambiguity, and understand that sometimes you have to throw away your own code.