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Intellias

Intellias is an AI-enabled product engineering and digital solutions partner. We help companies and professionals cut through complexity, focus on what matters, and deliver clear, measurable outcomes at scale.

Intellias is looking for a Python MCP Engineer to join the Core Architecture Team working on enterprise AI and cloud platform solutions.

In this role, you will design and develop services based on the Model Context Protocol (MCP), enabling seamless integrations between AI agents, enterprise systems, and external tools. You'll work with modern Python technologies, asynchronous architectures, cloud-native services on AWS, and observability solutions to build scalable, secure, and production-ready backend services.

If you're passionate about backend engineering, distributed systems, and the rapidly evolving AI ecosystem, this is an opportunity to work on innovative technologies used at enterprise scale.

About the project

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. The platform provides reusable services, infrastructure, security standards, and engineering best practices, enabling faster and more reliable development of enterprise applications, digital products, and IoT solutions.

As part of the Core Architecture Team, you will contribute to building the next generation of AI-powered platform capabilities focused on interoperability between AI agents, enterprise services, and cloud-native applications.

Responsibilities

  • 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

Requirements

  • 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

Why join Intellias?

At Intellias, you'll work on large-scale enterprise platforms that combine cloud technologies, AI, and modern software engineering practices. You'll collaborate with experienced engineers, contribute to architectural decisions, and help build solutions that support development teams operating on a global scale.

This role offers the opportunity to work with emerging AI integration technologies while solving complex engineering challenges in a collaborative international environment.

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