Job Location : Whippany, NJ (Onsite/Hybrid from Day 1)Job Description 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 have deep expertise in
Python, GenAI architectures, LLM orchestration frameworks, MCP implementations, API development, cloud-native services, and financial data integrations.
Key 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.
Required Qualifications - 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.
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 of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, 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
- Other benefits as provided by local policy and eligibility
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
