Tech Lead Engineer – Model Context Protocol (MCP) Integration
About the Role
We are looking for a Tech Lead Engineer to drive the design and implementation of enterprise-grade integrations based on the Model Context Protocol (MCP). This role combines Python backend engineering, protocol design, API governance, authentication, observability, and AI platform integration to enable secure and scalable communication between AI agents, tools, and enterprise services.
As a technical leader, you will define architecture standards, guide implementation across engineering teams, and lead the adoption of emerging agent communication protocols in a cloud-native environment. The ideal candidate has deep experience building distributed systems, designing APIs and contracts, implementing secure integrations, and mentoring engineers.
Project Overview
Our customer is a multinational corporation with more than a century of history and operations in over 180 countries. One of its key strategic initiatives is the development and adoption of a new generation of Reduced-Risk Products (RRPs), targeting more than one billion consumers worldwide.
Intellia partners with the customer to engineer a comprehensive software ecosystem supporting innovative IoT products, digital commerce, and enterprise platforms. Our engineering teams develop core platform components powering best-in-class eCommerce, Digital Marketing, and IoT solutions.
As a Tech Lead Engineer, you will become part of the Core Architecture Team, contributing to the design and implementation of a modern Digital Engineering Enterprise Platform.
The platform provides engineering teams with reusable services, cloud technologies, governance standards, and operational best practices that accelerate software delivery across more than 700 enterprise applications.
Responsibilities
- Lead the architecture, design, and implementation of MCP-based services and integrations using Python, Fast API, and FastMCP.
- Develop and maintain MCP servers, tool adapters, and protocol-compliant integration layers.
- Design and enforce Canonical Contracts, Open API specifications, and API governance standards.
- Build secure, scalable integrations with AWS AgentCore Gateway and related AI platform services.
- Implement enterprise authentication and authorization using OAuth 2.0, JWT, and AWS Signature Version 4 (SigV4).
- Design asynchronous APIs and service-to-service communication patterns supporting AI agent ecosystems.
- Establish observability standards and implement OpenTelemetry instrumentation for protocol interactions and service monitoring.
- Collaborate with AI platform teams to enable agent-to-tool and agent-to-agent communication capabilities.
- Define best practices for protocol versioning, backward compatibility, testing, and governance.
- Review architecture, design decisions, and implementation approaches across multiple engineering teams.
- Support Architecture Review Board (ARB), Information Security (InfoSec), and compliance processes.
- Mentor engineers and provide technical leadership for enterprise MCP adoption initiatives.
- Produce technical documentation, implementation guides, reference architectures, and engineering standards.
Requirements
- Bachelor's degree in computer science, Software Engineering, or a related field.
- 5+ years of professional Python backend engineering experience.
- Hands-on experience implementing Model Context Protocol (MCP) servers or comparable protocol-based integration frameworks.
- Strong experience developing RESTful and asynchronous APIs using FastAPI or similar Python frameworks.
- Experience building applications with FastMCP or equivalent MCP tooling.
- Experience integrating with AWS AgentCore Gateway or similar AI platform integration services.
- Strong knowledge of API design, Canonical Contracts, and OpenAPI specification development.
- Experience implementing enterprise authentication and authorization using OAuth 2.0, JWT, and AWS SigV4.
- Experience implementing observability using OpenTelemetry or similar monitoring frameworks.
- Strong understanding of distributed systems, cloud-native architecture, and service integration patterns.
- Excellent leadership, mentoring, communication, and stakeholder management skills.
Nice to Have
- Experience with AWS AgentCore Gateway or other enterprise AI integration platforms.
- Experience with AI agent frameworks such as LangGraph, Strands, or similar technologies.
- Experience supporting enterprise governance processes, including Architecture Review Boards (ARB) and Information Security (InfoSec) reviews.
- Experience with CI/CD pipelines, Infrastructure as Code (IaC), and cloud-native deployment practices.
- Familiarity with AI agent ecosystems, tool orchestration, and emerging agent communication standards.
Why Join Us
- Lead the adoption of the Model Context Protocol (MCP) across enterprise-scale AI platforms.
- Design and build secure, scalable integrations for next-generation AI agent ecosystems.
- Work with cutting-edge AWS AgentCore technologies, cloud-native architectures, and modern API standards.
- Collaborate with experienced AI, platform, cloud, and security engineering teams on global-scale initiatives.
- Shape engineering standards, protocol governance, and the future of enterprise AI integrations.
