MODULE LEAD - Python

Artificial Intelligence & Engineering

AI & Engineering leverages cutting-edge engineering capabilities to help build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These insights are powered by engineering for business advantage, helping transform mission-critical operations.

Join our AI & Engineering team to help transform technology platforms, drive innovation, and help make a significant impact on our clients' achievements. You'll work alongside talented professionals reimagining and re-engineering operations and processes that could be critical to businesses.

Position Summary

As a Consultant-level AI Developer (MCP Engineer) at Deloitte Consulting, you will design and build Model Context Protocol (MCP) servers in Python that expose enterprise system capabilities as reusable tools for AI agents built on platforms such as Microsoft Copilot Studio, Moveworks, and pro-code solutions like Azure AI Foundry.

Work you'll do

Design, build, and operate Python-based MCP servers that expose enterprise system capabilities as reusable tools for AI agents, and support the Azure AI Search pipelines that ground them in enterprise knowledge.

Design and build Python-based MCP servers (using frameworks such as FastMCP) exposing enterprise system capabilities as reusable tools

Implement authentication patterns for MCP tool calls, including on-behalf-of (OBO) token exchange and non-interactive client credentials flows

Integrate MCP servers with enterprise REST APIs (such as ServiceNow, UKG Pro WFM, and similar systems)

Deploy and operate MCP servers on Azure Container Apps, including environment configuration and secret management

Build and maintain Azure AI Search ingestion and retrieval pipelines (data sources, indexers, skillsets, and semantic/vector search configuration) to support knowledge grounding for AI agents

Write unit and integration tests for MCP tool logic

Collaborate with the AI Tech Lead on base MCP server patterns that can be cloned and reused across new capability areas

Participate in sprint planning and backlog refinement for MCP-related stories

The team

Within AI & Engineering, our Workplace Engineering practice designs, builds, and operates AI agents across a range of platforms for enterprise clients, including low-code solutions such as Microsoft Copilot Studio and Moveworks, and pro-code solutions such as Azure AI Foundry, combining conversational AI, Power Platform engineering, and Model Context Protocol (MCP) server development to deliver secure, scalable AI assistants. Current work includes large-scale Copilot Studio deployments for enterprise clients, supporting tens of thousands of employees across HR, IT, benefits, and workforce self-service use cases.

Qualifications

Must Have Skills/Project Experience/Certifications:

3+ years of relevant consulting or industry experience

Strong Python development skills

Experience building or consuming REST APIs, including OAuth 2.0 authentication (bearer tokens, token exchange)

Experience with cloud-hosted applications (Azure Container Apps, Azure Functions, or equivalent)

Understanding of Model Context Protocol (MCP) or similar tool-exposure frameworks

Good interpersonal and communication skills

Good to Have Skills/Project Experience/Certifications:

Experience with Microsoft Copilot Studio or other conversational AI platforms

Experience with Azure AI Search (or equivalent vector/semantic search) pipeline configuration

Experience with Azure API Management

Familiarity with Microsoft Entra ID application registrations and service principals

Experience integrating with HR, ITSM, or workforce management systems (e.g. ServiceNow, UKG, Workday)

Education

B.E./B.Tech/M.C.A./M.Sc (CS) degree or equivalent from accredited university

Location

Bengaluru/Hyderabad