Python MCP Engineer
Location: Remote / Global
Engagement: Staff Augmentation through Intellias
Department: Core Architecture / Digital Engineering Platform
Degree: Bachelor’s Degree
Experience: 4+ years
About the Role
We are looking for a Python MCP Engineer to join our customer’s Core Architecture Team and build and maintain Model Context Protocol (MCP) services that power integrations between AI agents, tools, and enterprise platforms.
The role focuses on Python backend engineering, asynchronous APIs, MCP server implementation, observability, and secure cloud-native deployments on AWS. The ideal candidate has strong Python engineering skills, experience building API-driven integrations, and a solid understanding of modern distributed systems.
You will contribute to a next-generation digital engineering platform designed to accelerate software development and delivery by providing engineering teams with reusable services, technologies, practices, and capabilities while ensuring compliance, security, and engineering best practices.
Project Overview
Our customer is a multinational corporation with more than a century of history, operating across 180+ countries and serving more than 1 billion consumers worldwide.
The organization is undergoing a major transformation focused on introducing a new generation of Reduced-Risk Products (RRPs) supported by innovative digital, IoT, eCommerce, and marketing technologies. Its IT landscape includes 700+ applications.
Intellias supports the engineering of a comprehensive software ecosystem for a game-changing IoT product at the intersection of innovative consumer experiences and cutting-edge technology.
As a Python MCP Engineer, you will become part of the Core Architecture Team, contributing to the architecture, implementation, and continuous improvement of the Digital Engineering Enterprise Platform.
The platform provides engineering teams with standardized services and technologies that accelerate application development and operations while addressing common SDLC challenges and enforcing security, compliance, and best practices.
Key Responsibilities
MCP & Backend Engineering
- Design, develop, and maintain MCP servers using Python, FastMCP, and modern asynchronous frameworks.
- Implement MCP protocol functionality and server-side communication patterns.
- Build scalable and maintainable backend services using FastAPI, asyncio, and Pydantic.
- Develop API-driven integrations connecting AI agents, enterprise services, internal systems, and external tools.
- Design robust schemas, validation logic, API contracts, and integration interfaces.
- Ensure reliable interoperability between AI agents and enterprise tools.
AWS & Cloud-Native Development
- Deploy and operate backend and MCP services on AWS.
- Build serverless solutions using AWS Lambda and API Gateway.
- Design services for scalability, reliability, availability, and maintainability.
- Support cloud-native deployment patterns and operational best practices.
- Troubleshoot production issues and continuously improve service reliability and performance.
Security & Observability
- Implement secure containerized workloads following established security baselines and hardening standards.
- Apply secure coding and deployment practices across backend and integration services.
- Implement observability using OpenTelemetry, including:
- Distributed tracing
- Metrics
- Structured logging
- Monitor service health, performance, and integration reliability.
- Use telemetry and operational data to identify and resolve performance or reliability issues.
Testing & Documentation
- Build automated testing and validation mechanisms for API and integration workflows.
- Maintain high-quality API contracts, schemas, technical documentation, and integration specifications.
- Ensure services meet engineering, security, and operational standards.
- Contribute to reusable engineering patterns and best practices across the platform.
Collaboration
- Collaborate with AI platform, architecture, cloud, and engineering teams to enable seamless agent and tool interoperability.
- Work closely with technical stakeholders to understand integration requirements and translate them into scalable solutions.
- Participate in technical discussions, architecture decisions, code reviews, and continuous improvement initiatives.
- Contribute to the evolution of the enterprise platform and its AI integration capabilities.
Required Qualifications & Experience
- Bachelor’s degree in computer science, Software Engineering, Information Technology, or a related field.
- 4+ years of professional Python development experience.
- Strong hands-on experience with:
- Python
- FastMCP
- asyncio
- Pydantic
- Experience implementing or developing MCP servers / Model Context Protocol integrations.
- Strong experience building API-driven integrations and backend services.
- Hands-on experience with asynchronous Python frameworks such as FastAPI or aiohttp.
- Experience with AWS Lambda and API Gateway.
- Understanding of distributed systems and cloud-native architectures.
- Experience implementing observability with OpenTelemetry, including traces, metrics, and logs.
- Understanding of container security, baseline hardening, and secure deployment practices.
- Strong understanding of API design, schemas, validation, and integration patterns.
- Strong troubleshooting and problem-solving skills.
- Good English communication and collaboration skills.
Nice-to-Have Qualifications
- Hands-on experience with the FastMCP library.
- Experience integrating tools with LangGraph.
- Exposure to AWS Bedrock or Amazon Bedrock AgentCore.
- Experience building AI-agent integrations or tool-calling workflows.
- Experience with containerized workloads and Docker/Kubernetes.
- Experience working within enterprise engineering platforms or internal developer platforms.
- Knowledge of CI/CD, infrastructure automation, and DevOps practices.
Key Technical Skills
Python | FastMCP | MCP | asyncio | FastAPI | aiohttp | Pydantic | AWS Lambda | API Gateway | OpenTelemetry | REST APIs | API Integration | Distributed Systems | Container Security | Cloud-Native Development | AI Agents | LangGraph | AWS Bedrock
Why This Position?
- Work at the intersection of AI and enterprise engineering: Build MCP services that enable AI agents to securely interact with enterprise systems and tools.
- Solve complex engineering challenges: Work on distributed, cloud-native services operating within a large global technology ecosystem.
- Global scale: Contribute to platforms supporting an organization with 700+ applications across 180+ countries.
- Cutting-edge technology: Gain hands-on exposure to MCP, AI agents, FastMCP, AWS, observability, and modern backend architectures.
- Architecture impact: Join the Core Architecture Team and contribute to reusable engineering standards and platform capabilities.
- Innovation at scale: Help build the technology ecosystem behind next-generation IoT, eCommerce, and digital experiences.
- Continuous growth: Work alongside experienced engineers and architects in a highly collaborative international environment.
- Intellias partnership: Join through Intellias and contribute to a long-term enterprise technology transformation.
Education
Bachelor’s degree in computer science, Software Engineering, Information Technology, or a related technical field.