Python MCP Engineer

Our client is a global enterprise operating in more than 180 countries with a portfolio of over 700 business applications. Intellias supports the client in developing a comprehensive Digital Engineering Platform that accelerates software delivery across multiple engineering teams by providing reusable services, infrastructure, security standards, and engineering best practices. The Core Architecture Team focuses on building AI-powered platform capabilities for interoperability between AI agents, enterprise services, and cloud-native applications.

• 4+ years of professional experience with Python
• Strong experience building backend services and API integrations
• Hands-on experience with asynchronous Python frameworks such as FastAPI or aiohttp
• Experience with FastMCP
• Strong knowledge of asyncio and Pydantic
• Experience implementing server-side MCP services
• Practical experience with AWS Lambda and API Gateway
• Understanding of distributed systems and API-driven architectures
• Experience with OpenTelemetry (traces, metrics, logs)
• Knowledge of container security best practices
• Strong problem-solving skills and ability to work independently
• Good communication skills and English proficiency suitable for an international environment

Nice to have:

• Experience with LangGraph integrations
• Exposure to AWS Bedrock or AgentCore
• Experience working with AI agent frameworks
• Familiarity with cloud-native architectures and enterprise integration platforms

• Design, develop, and maintain MCP servers using Python and FastMCP
• Build API-driven integrations between AI agents, enterprise platforms, and external services
• Develop scalable backend services using FastAPI, asyncio, and Pydantic
• Implement Model Context Protocol (MCP) server-side functionality
• Deploy and maintain cloud-native services on AWS using Lambda and API Gateway
• Build secure containerized workloads following security best practices
• Implement observability with OpenTelemetry, including tracing, metrics, and structured logging
• Create and maintain API contracts, schemas, validation logic, and technical documentation
• Optimize application performance, scalability, and reliability
• Develop automated testing for integration workflows
• Collaborate with AI platform and engineering teams to enable reliable tool integration
• Troubleshoot production issues and continuously improve platform services

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