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We are seeking a skilled Backend Software Engineer to build and maintain production-ready Model Context Protocol (MCP) servers that power our AI agent workflows. This role focuses on the Internal AI platform, requiring you to design distributed systems using Python, FastMCP, and Redis with enterprise-grade security.
Job Responsibility:
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
Requirements:
Strong proficiency in Python with deep knowledge of async/await patterns
Solid experience with FastAPI and REST API design
Proven experience building MCP servers (critical requirement)
Hands-on experience with FastMCP framework
Proficiency with Relational Databases (SQL) and Key-Value stores (Redis)
Deep understanding of AuthN/AuthZ protocols
Experience with OAuth2, Azure Entra ID/SSO, and JWT token handling
Familiarity with Distributed Systems and Event-Driven Architecture
Experience with Docker and containerization principles
Strong problem-solving capabilities
Ability to work independently and communicate technical concepts clearly
Nice to have:
Orientation in the broader ecosystem of MCP applications and clients
Experience with AI/LLM agent frameworks such as LangGraph, LangChain, or Langfuse
Familiarity with Azure CI/CD pipelines and GitHub Actions
Knowledge of Datadog or similar platforms for logging and monitoring
Prior exposure to „Vibe” coding practices (AI-assisted iterative coding)