Location: Hanover, NJ.Key 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
Basic Qualifications To be successful in this role you should have- 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 CICD 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
The base compensation range for this role in the posted location is: $105,000 - $115,000
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
