AI Engineer (MPC + Agents)

O projekcie: - Private medical care - Co-financing for the sports card - Training & learning opportunities - Constant support of dedicated consultant - Employee referral program Wymagania: - Core Development: Strong proficiency in Python with deep knowledge of async/await patterns - Solid experience with FastAPI and REST API design - MCP Specialization: Proven experience building MCP servers (critical requirement) - Hands-on experience with FastMCP framework - Data & Storage: Proficiency with Relational Databases (SQL) and Key-Value stores (Redis) - Security (IAM): Deep understanding of AuthN/AuthZ protocols. Experience with OAuth2, Azure Entra ID/SSO, and JWT token handling - Architecture: Familiarity with Distributed Systems and Event-Driven Architecture - Experience with Docker and containerization principles - Soft Skills: Strong problem-solving capabilities. Ability to work independently and communicate technical concepts clearly Nice to have: - MCP Ecosystem: Orientation in the broader ecosystem of MCP applications and clients - AI Frameworks: Experience with AI/LLM agent frameworks such as LangGraph, LangChain, or Langfuse - DevOps: Familiarity with Azure CI/CD pipelines and GitHub Actions - Observability: Knowledge of Datadog or similar platforms for logging and monitoring - Modern Practices: Prior exposure to "Vibe" coding practices (AI-assisted iterative coding) Codzienne zadania: - Build MCP Servers: Design, build, and maintain high-performance servers using the FastMCP framework, ensuring reliability and maintainability - REST API Design: Design and implement RESTful APIs with strict adherence to OpenAPI/Swagger standards, focusing on proper endpoint structure and error handling - Async Programming: Write clean, efficient Python code utilizing asyncio and httpx for non-blocking I/O operations - Orchestration Systems: Implement and extend agentic workflow orchestration systems, utilizing - Event-driven architectures and webhook integrations - State Management: Leverage Redis for distributed state persistence, caching strategies, and TTL-based data management - System Reliability: Troubleshoot and debug complex issues across the distributed system stack to ensure uptime and performance - Enterprise Security: Implement robust security features, including OAuth2 flows, Azure Entra ID (SSO) integration, and secure JWT token validation - Testing & QA: Build and maintain comprehensive test suites (unit, integration, and E2E) using pytest and pytest-asyncio - Containerization: Containerize applications using Docker and manage local/prod environments via docker-compose and Azure pipelines