Senior Python Backend Engineer

We are looking for a highly skilled Senior Backend Engineer to join a specialized team building a core evaluation platform for a German-based client.This system is a critical component of the AI lifecycle, allowing for the comprehensive testing of AI agents through simulated scenarios and real-time performance tracking.If you are passionate about the intersection of high-performance backend engineering and the rapidly evolving world of AI, this is the project for any developer looking for a long-term challenge.As a Senior Engineer, you will take full responsibility for developing and scaling backend services. You will work alongside technical leaders and an internal development team to ensure that microservices are high-performance, low-latency, and reliable. This role requires a proactive approach to system design and the ability to handle the 'end-to-end' lifecycle of a feature, from initial requirements analysis to production deployment.DetailsRate: 140 – 170 PLN/h net + VAT (B2B).Duration: Contract through the end of 2026 (strong extension potential).Location: 100% RemoteCollaboration: Part of a dedicated squad of 4–5 engineers.On-site Opportunities: Optional 'team weeks' in Berlin (roughly twice a quarter for 3–5 days). These visits are not mandatory but are encouraged for team integration.ResponsibilitiesPython Expertise: At least 3 years of experience with modern Python (3.10+), including deep knowledge of asyncio and asynchronous programming.Backend Track Record: 7+ years of professional experience building production-grade backend services.System Design: Proven ability to design and implement REST APIs and scalable distributed systems.Event-Driven Knowledge: Experience with task queues, message brokers, and designing systems resistant to heavy loads.Data Management: Production experience with NoSQL (specifically MongoDB), including schema design and query optimization.Ownership: A strong sense of responsibility for the code you deliver and the ability to communicate technical risks clearly in English.Requirements Frameworks: FastAPI, Uvicorn, Pydantic.Infrastructure: MongoDB (Motor), Redis, Kafka/Azure Event Hubs.Cloud & DevOps: Kubernetes, Docker, GitHub Actions, ArgoCD.Observability: OpenTelemetry, Datadog, structured logging.AI Integration: Working with OpenAI SDKs and managing token usage/costs.