GenAI Platform Engineer; Python, MCP & Agentic AI

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired bya collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

We are seeking a highly skilled GenAI Platform Engineer to design, develop, and scale next-generation AI-powered solutions that support investment banking and financial services workflows. This role will focus on building enterprise-grade Generative AI platforms, agentic workflows, Model Context Protocol (MCP) integrations, Retrieval-Augmented Generation (RAG) capabilities, and secure backend services that enable business users to leverage AI solutions in a controlled, governed, and production-ready environment.

• Design, develop, and maintain Python-based GenAI services, agent workflows, MCP integrations, and reusable platform components.
• Build MCP servers, clients, tools, resources, prompts, schemas, and authorization frameworks.
• Develop agent orchestration workflows including tool calling, function calling, retrieval, workflow execution, and output generation.
• Design and implement RAG pipelines covering ingestion, embeddings, retrieval, ranking, answer synthesis, and citations.
• Integrate internal and external data sources, including financial data providers, SEC filings, enterprise repositories, web search, and banking platforms.
• Develop secure, production-grade APIs and backend services using Python, FastAPI, and asynchronous programming.
• Implement authentication, authorization, entitlement controls, logging, monitoring, testing, and model output validation.
• Collaborate with business stakeholders, architects, cloud engineers, and governance teams to deliver production-ready AI solutions.
• Create and maintain technical documentation, architecture designs, and operational procedures.

• Bachelor's degree in Computer Science, Engineering, AI, or a related technical field (or equivalent experience).
• Strong hands-on experience with Python backend development.
• Proven experience building GenAI applications, LLM workflows, agentic systems, or AI-powered platforms.
• Experience with MCP concepts and implementations, including tools, resources, servers, and clients.
• Experience with Lang Chain, Lang Graph, or similar orchestration frameworks.
• Strong understanding of RAG, embeddings, vector search, retrieval quality, and grounding techniques.
• Experience developing APIs using FastAPI, REST, and async Python.
• Knowledge of Git, CI/CD, testing frameworks, and cloud deployment practices.
• Experience with AWS and containerized applications.
• Understanding of enterprise security, authentication, authorization, and secrets management.
• Experience in banking, financial services, capital markets, or other regulated environments preferred.

• Experience with AWS Bedrock, Claude models, and managed GenAI services.
• Experience integrating Fact Set, Bloomberg, S&P Capital IQ, Refinitiv, Fitch, or similar data providers.
• Knowledge of Open Search, Pinecone, pg Vector, Weaviate, Chroma, or other vector databases.
• Familiarity with Open Telemetry, observability, AI evaluation frameworks, and prompt management.
• Understanding of AI governance, model risk management, data privacy, and regulatory controls.
• Exposure to investment banking workflows including IPOs, ECM, DCM, M&A, and advisory processes.

The base compensation range for this role in the posted location is:90786- 107298

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside…