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Jobs · Engineering · New York

GenAI Platform Engineer (Python, MCP & Agentic AI)

Capgemini · New York, United States · 2 mo ago
EngineeringFull-time

About the role

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.

The ideal candidate will join a collaborative global community and help leading organizations unlock the value of technology to build a more sustainable, more inclusive world. This position is based in Whippany, NJ and offers onsite/hybrid work from day one.

Responsibilities

  • 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.

Requirements

  • 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 LangChain, LangGraph, 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.

Preferred Qualifications

  • Experience with AWS Bedrock, Claude models, and managed GenAI services.
  • Experience integrating FactSet, Bloomberg, S&P Capital IQ, Refinitiv, Fitch, or similar data providers.
  • Knowledge of OpenSearch, Pinecone, pgVector, Weaviate, Chroma, or other vector databases.
  • Familiarity with OpenTelemetry, 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.

Pay

The base compensation range for this role in Whippany, NJ is $90,786 – $107,298. Actual compensation may vary based on factors including geographic location, education, qualifications, certifications, relevant experience, skills, seniority, performance, market considerations, and internal pay equity.

Benefits

  • Paid time off: 12–25 vacation days (depending on grade), company-paid holidays, personal days, and sick leave.
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada).
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada).
  • Life and disability insurance.
  • Employee assistance programs.
  • Additional benefits as provided by local policy and eligibility.

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