MCP Python Engineer

Actively Reviewing the Applications

Agivant Technologies

India, Maharashtra Full-Time

Posted 12 hours ago • Apply by June 17, 2026

Job Description

Job Description

We are seeking a highly skilled Python Software Engineer to spearhead the development of our Model Context Protocol (MCP) infrastructure. In this role, you will build the "connective tissue" between our internal software services and AI agents. You will be responsible for designing high-performance REST services and transforming them into MCP Servers, enabling autonomous AI agents to interact with our data and tools securely and efficiently.

Key Responsibilities

MCP Server Development & Integration
Build and maintain high-performance MCP servers using Python, FastAPI, and asyncio to bridge the gap between AI models and internal data.
Develop reusable MCP components that interface with diverse enterprise systems, including REST APIs, GraphQL, and gRPC.
Expose complex data platforms—such as Snowflake, Azure Data Lake, and Kafka—as structured MCP Resources for model consumption.
AI Orchestration & Multi-Agent Workflows
Design and implement scalable server architectures using LangChain and LangGraph to facilitate sophisticated multi-agent coordination.
Architect custom Tools and Resources via the MCP SDK, allowing agents to perform real-time data retrieval and autonomous task execution.
Security, Scalability & Performance
Implement Zero Trust security architectures and robust OAuth authentication flows to ensure secure data access.
Optimize system performance and state management using Redis for caching and PostgreSQL for persistent storage.
Manage the full deployment lifecycle using Docker and Kubernetes to ensure high availability and horizontal scalability

Requirements

Technical Qualifications

Python Mastery: 5+ years of experience with Python, with expert-level knowledge of asyncio and FastAPI.
AI Protocols: Proven experience working with the Model Context Protocol (MCP) and building custom MCP servers.
Orchestration: Hands-on experience with LangChain and LangGraph for building agentic workflows.
Data Systems: Proficiency in querying and integrating with Snowflake, SQL/NoSQL databases, and real-time streams like Kafka.
Infrastructure: Deep experience with Docker, Kubernetes, and CI/CD pipelines.
Security: Strong understanding of enterprise security patterns (mTLS, JWT, RBAC, and Zero Trust).