Inactive
C

Capgemini

Global consulting, technology services, outsourcing

Agentic AI Lead

AI Application Engineering +1Posted on Nov 11
Full-timeNew York, NY, USA

About the Job

Requirements

  • Strong hands-on experience in Python development.
  • Experience with OpenAI, Azure OpenAI, AWS Bedrock, Anthropic Claude, Gemini, Llama, or Mistral.
  • Hands-on experience with at least one agentic framework: LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, or LlamaIndex.
  • Good understanding of retrieval-augmented generation (RAG), embeddings, vector databases, semantic search, and prompt engineering.
  • Experience with vector stores such as OpenSearch, Pinecone, FAISS, Chroma, Weaviate, Milvus, Azure AI Search, or pgvector.
  • Knowledge of REST APIs, cloud deployment, Docker, continuous integration and continuous delivery (CI/CD), and software engineering best practices.
  • Ability to work with structured and unstructured data, including PDFs, documents, APIs, databases, and knowledge bases.
  • Ability to clearly explain at least one end-to-end GenAI or Agentic AI project, including its problem statement, architecture, tools used, deployment approach, evaluation method, and business impact.

Responsibilities

  • Build generative AI applications using large language models (LLMs), RAG, agents, and tool-calling workflows.
  • Develop agentic solutions using LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or LlamaIndex.
  • Design and implement multi-agent workflows such as planner, retriever, executor, validator, and human-in-the-loop agents.
  • Build backend APIs using Python, FastAPI, Flask, REST APIs, and microservices.
  • Integrate AI agents with enterprise systems, databases, APIs, document repositories, and cloud services.
  • Implement document ingestion, embeddings, vector search, reranking, and retrieval pipelines.
  • Deploy and monitor GenAI applications using Docker, Kubernetes, CI/CD, and cloud platforms.
  • Support LLMOps, including prompt and version management, model evaluation, monitoring, logging, and cost tracking.

Desired Qualifications

  • Experience with multi-agent orchestration, tool calling, memory, planning, reflection, and evaluation.
  • Exposure to MCP, Graph RAG, Neo4j, knowledge graphs, or entity extraction.
  • Knowledge of LLMOps tools such as LangSmith, MLflow, Phoenix, Ragas, TruLens, Arize, or OpenTelemetry.
  • Experience with AWS Bedrock or SageMaker, Azure OpenAI or AI Search, or GCP Vertex AI.
  • Understanding of AI guardrails, prompt injection prevention, PII masking, access control, and responsible AI.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

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