MCP Lead Developer

Role & responsibilities

Role Summary

We are seeking an experienced MCP Lead Developer with strong Python expertise to design, build, test, and operate Model Context Protocol (MCP) servers and tools. This role is responsible for owning the full MCP lifecycle, including server implementation, tool creation, test agent development, validation, and performance testing.

The ideal candidate combines handson engineering, technical leadership, and AIintegration experience, with the ability to guide teams and ensure MCP platforms are reliable, secure, and productionready.

Key Responsibilities

MCP Architecture & Development

• Lead the design and implementation of MCP servers using Python.
• Build and maintain MCP tools that expose backend capabilities to AI/LLM clients.
• Own MCP server architecture, including:
• Tool registration and invocation
• Resource and context lifecycle management
• Secure communication patterns
• Ensure MCP implementations align with scalability, reliability, and performance requirements.

MCP Testing & Validation (Critical Responsibility)

• Design and develop test agents to validate MCP server behavior.
• Create automated functional, integration, and regression tests for MCP servers and tools.
• Build test agents that simulate:
• AI clients
• Tool invocations
• Context and resource exchanges
• Execute and validate MCP servers across:
• Local development environments
• CI/CD pipelines
• Cloud deployments
• Perform performance and load testing of MCP servers and tools.
• Troubleshoot MCP issues across runtime, tool execution, and agent interactions.

Python Development Skills

• Strong handson experience with Python for:
• MCP server development
• Automation and scripting
• Test agent implementation
• Experience designing clean, maintainable, and testable Python codebases.
• Familiarity with asynchronous programming and concurrency in Python.

CI/CD, DevOps & Cloud

• Integrate MCP servers, tools, and test agents into CI/CD pipelines.
• Automate build, test, and deployment workflows.
• Experience working with Docker and containerized environments.
• Deploy and operate MCP servers in cloud platforms.
• Implement logging, monitoring, and observability for MCP runtimes.

AI & Agent Integration

• Experience integrating MCP servers with LLMbased systems and agent frameworks.
• Understanding of agentdriven workflows and toolcalling patterns.

Preferred candidate profile