GenAI/Agentic AI Developer

Responsibilities

• Design and develop GenAI solutions using LLMs, RAG, tool calling, and agent-based architectures
• Build and orchestrate multi-agent workflows, including planner, retriever, executor, and validator patterns
• Develop backend services and APIs using Python, FastAPI, Flask, and microservices
• Design and implement document ingestion, embedding generation, and vector indexing pipelines
• Integrate AI applications with enterprise systems, databases, and cloud services
• Deploy and monitor GenAI applications using Docker, Kubernetes, and CI/CD pipelines
• Implement LLMOps best practices, including model evaluation, prompt management, and observability

Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
• 5+ years of hands-on Python development experience
• Experience building and deploying GenAI or Agentic AI applications in enterprise environments
• Hands-on experience with frameworks such as LangChain, LlamaIndex, LangGraph, or AutoGen
• Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, and prompt engineering
• Experience with vector databases such as Pinecone, Milvus, Weaviate, or Chroma
• Experience developing REST APIs and cloud-native applications

Preferred Qualifications

• Experience designing and deploying multi-agent AI systems with autonomous planning and reflection
• Exposure to GraphRAG, Knowledge Graphs, or Neo4j
• Experience with LLMOps tools like LangSmith, MLflow, or Ragas
• Proficiency with cloud AI platforms such as Azure OpenAI, AWS Bedrock, or GCP Vertex AI
• Knowledge of AI governance, responsible AI, and prompt injection prevention

About the Company

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. We help our clients navigate the complexities of the digital age through cutting-edge innovation in Data & AI.