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Capgemini · New York

# GenAI / Agentic AI Developer

New York Software Engineering 

Listed on Capgemini’s official careers site. Listed as of October 18, 2026. Check that it is still open and apply there.
[Apply on Capgemini’s careers site →](https://www.capgemini.com/jobs/506367-en_US+sap_btp)

[OpenNash Jobs](https://jobs.opennash.com/) / [Capgemini](https://jobs.opennash.com/companies/capgemini/) / GenAI / Agentic AI Developer

## Job description

Work AuthorizationCandidates must be authorized to work in the United States without current or future employer sponsorship.Visa sponsorship is not available for this position. Candidates requiring sponsorship now or in the future, including H-1B, OPT, CPT, F-1, TN, E-3, L-1, or similar employment-based sponsorship, are not eligible for consideration.Job DescriptionWe are seeking a highly skilled and hands-on GenAI / Agentic AI Developer to design, build, and deploy enterprise-grade AI solutions powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures.The ideal candidate will have strong Python development expertise and practical experience implementing GenAI applications, agent orchestration frameworks, vector search technologies, and cloud-native AI solutions.

This role requires someone who can move from proof-of-concept to production while ensuring scalability, reliability, security, and business value.Key ResponsibilitiesDesign and develop GenAI solutions using LLMs, RAG, tool calling, and agent-based architectures.Build and orchestrate multi-agent workflows, including planner, retriever, executor, validator, and human-in-the-loop patterns.Develop backend services and APIs using Python, FastAPI, Flask, REST APIs, and microservices.Design and implement document ingestion, embedding generation, vector indexing, reranking, and retrieval pipelines.Integrate AI applications with enterprise systems, APIs, databases, document repositories, and cloud services.Deploy, monitor, and support

GenAI applications using Docker, Kubernetes, CI/CD pipelines, and cloud platforms.Implement LLMOps best practices, including model evaluation, prompt management, monitoring, logging, observability, and cost optimization.Collaborate with business and technology stakeholders to deliver scalable AI solutions that generate measurable business outcomes.Required QualificationsBachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent professional experience.5+ years of hands-on

Python development experience.Experience building and deploying GenAI or Agentic AI applications in enterprise environments.Hands-on experience with one or more of the following: LangGraphLangChainAutoGenCrewAISemantic KernelLlamaIndexStrong understanding of: Retrieval-Augmented Generation (RAG)EmbeddingsPrompt EngineeringSemantic SearchVector DatabasesExperience working with one or more of the following: OpenAIAzure OpenAIAWS BedrockAnthropic ClaudeGeminiLlamaMistralExperience with vector platforms such as: OpenSearchPineconeChromaFAISSWeaviateMilvusAzure AI SearchpgvectorExperience developing REST APIs and cloud-native applications.Knowledge of

Docker, Kubernetes, CI/CD, and software engineering best practices.Experience working with structured and unstructured data sources, including documents, PDFs, APIs, databases, and knowledge repositories.Preferred QualificationsExperience designing and deploying multi-agent AI systems.Experience with tool calling, memory management, autonomous planning, reflection, and evaluation techniques.Exposure to:MCP (Model Context Protocol)

GraphRAGNeo4jKnowledge GraphsEntity ExtractionExperience with LLMOps tools such as: LangSmithMLflowPhoenixRagasTruLensArizeOpenTelemetryExperience with: Azure AI FoundryAzure OpenAIAzure AI SearchAWS BedrockAWS SageMakerGCP Vertex AIKnowledge of AI governance, responsible AI, AI guardrails, prompt injection prevention, PII masking, and access controls.Required Candidate ExperienceCandidates must be able to clearly explain at least one end-to-end GenAI or Agentic AI implementation, including: Business problem being solvedOverall solution architectureLLMs and frameworks leveragedAgent orchestration approachRAG and vector search designDeployment strategyEvaluation and monitoring methodologyBusiness impact and measurable outcomesFor this role, the gross annual starting base salary is 100,000–150,000 (full-time).

This covers base pay only; any bonuses, incentives, and benefits will be discussed later in the recruitment process. Candidates with additional experience or qualifications may receive a higher offer, determined by objective, gender-neutral criteria and consistent with our pay principles. If a collective labour agreement applies, we will explain the relevant pay terms at the interview stage.

### Note

We never ask for your current or previous salary during our hiring process.

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Aug 1, 2026
- Last checked: Oct 18, 2026
- Listed for: 78 days
- Location: New York[Apply on Capgemini’s careers site →](https://www.capgemini.com/jobs/506367-en_US+sap_btp)

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