Senior GenAI Python Engineer for Enterprise MCP

Capgemini; Whippany (NJ); On-site; USD 140,000 - 180,000; Full time

Job summary

Capgemini Whippany seeks a Senior Python Developer to design, build, and deploy GenAI features on the MCP platform. You will create Python‑based GenAI services, MCP servers, and agent workflows with secure enterprise integration.

You will implement RAG pipelines, orchestrate AI workflows, and integrate diverse data sources while ensuring production‑readiness, testing, and robust monitoring.

Qualifications

• Strong, hands-on experience in Python for backend, ML, or GenAI application development.
• Proven experience building GenAI applications, LLM workflows, agentic systems, or AI-enabled production services.
• Solid understanding of MCP concepts and practical implementation patterns for tools, resources, prompts, servers, and clients.
• Experience with LLM orchestration frameworks such as LangChain, LangGraph or similar.
• Strong understanding of RAG, vector search, embeddings, retrieval quality, citations, and grounding patterns.
• Experience developing APIs and backend services using FastAPI, REST APIs, async Python, and service-to-service integration patterns.
• Working knowledge of Git, modern version-control practices, CI/CD workflows, and test automation.
• Experience deploying or integrating containerized services in a cloud environment, preferably AWS.
• Good understanding of authentication, authorization, secrets handling, entitlements, and enterprise security patterns.
• Ability to independently debug complex distributed systems across APIs, data flows, cloud services, prompts, and model outputs.
• Prior experience in banking, financial services, capital markets, or other regulated technology environments.
• Bachelor degree in a quantitative or technical discipline such as Computer Science, Engineering, AI or equivalent experience.
• Minimum 7 years of hands-on Python development experience and 1+ year of Generative AI experience with successful implementation in production projects

Responsibilities

• Design, develop, enhance, and maintain Python‑based GenAI services, agent workflows, MCP integrations, and reusable platform capabilities.
• Build MCP servers, clients, tools, resources, prompts, schemas, and authorization patterns for internal and third‑party systems.
• Implement agent orchestration flows including tool calling, function calling, workflow execution, retrieval, and output generation.
• Integrate internal and external data sources such as financial data providers, SEC filings, web search, enterprise repositories, and banking data services into agent workflows.
• Design and implement RAG pipelines covering ingestion, chunking, embeddings, retrieval, ranking, answer synthesis, and citations.
• Develop production‑grade backend services and APIs using Python, FastAPI, async programming patterns, and secure service integration practices.
• Implement authentication, authorization, entitlement checks, and secure access patterns for user‑specific consumption of MCP‑enabled services.
• Perform testing, debugging, prompt evaluation, model‑output validation, logging, monitoring, and operational telemetry for GenAI components.
• Work closely with product owners, business analysts, architects, cloud engineers, governance teams, and bankers to convert requirements into production‑ready AI capabilities.
• Maintain clear documentation of technical design, assumptions, interfaces, limitations, failure modes, and operating considerations.

Skills

Python backend development

GenAI应用

Education

Bachelor degree in Computer Science or Engineering

Tools

LangChain

LangGraph

FastAPI

Git

CI/CD

AWS

Job description

Capgemini Whippany seeks a Senior Python Developer to design, build, and deploy GenAI features on the MCP platform. You will create Python‑based GenAI services, MCP servers, and agent workflows with secure enterprise integration.

You will implement RAG pipelines, orchestrate AI workflows, and integrate diverse data sources while ensuring production‑readiness, testing, and robust monitoring.