MCP Platform Engineer

We are looking for hands-on Python engineers to build and integrate Model Context Protocol (MCP) connectors and agent-facing tools that enable AI systems to interact with enterprise services.

This is a backend / integrations role first, focused on building scalable services, APIs, and reusable tooling that power AI-driven workflows.

• Build and maintain MCP connectors and services used by AI agents
• Integrate existing connectors into agent workflows
• Design and implement tools that agents call (APIs, schemas, handlers)
• Develop JSON-RPC / API-based communication layers
• Implement authentication, rate limiting, retries, and error handling
• Build scalable, reusable integration frameworks
• Work closely with AI teams to ensure tools are usable within agent workflows
• Contribute to how systems execute and respond within agent-driven environments

• 5-7 years (up to :9 max) of hands-on software engineering experience
• Strong Python (core/backend development)
• Experience building APIs, integrations, or developer tools
• Experience with async programming, concurrency, and scalable services
• Hands-on experience with MCP or similar protocol-based integrations
• Strong understanding of:
  • API design
  • request/response flows
  • system behavior in production
• Ability to clearly explain what they built and how it works end-to-end
• Experience building tools/services used by other systems (not just consuming APIs)

• Experience working with LLMs or AI agent workflows
• Understanding of:
  • tool calling
  • agent workflows
  • structured outputs / schemas
• Exposure to:
  • LangChain / LangGraph / similar frameworks
  • OpenAI, Bedrock, or other LLM APIs
• Experience integrating systems into AI-driven workflows

• Primary: Python
• APIs: REST, JSON-RPC
• Concepts: async/await, retries, rate limiting, authentication (OAuth/JWT)
• Bonus: Node.js, LLM frameworks, MCP implementations