About The Position

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

Requirements

  • Strong proficiency in Python and API development.
  • Experience building applications with Large Language Models (LLMs) and Generative AI technologies.
  • Hands-on experience with AI Agents, Multi-Agent Systems, and RAG architectures.
  • Knowledge of vector databases, embeddings, semantic search, and knowledge retrieval.
  • Experience with AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, or similar.
  • Familiarity with prompt engineering, model evaluation, and AI application monitoring.
  • Understanding of software engineering best practices, including Git, CI/CD, testing, and cloud-native architectures.
  • Knowledge of AI governance, security, privacy, and Responsible AI principles.

Responsibilities

  • Design, develop, and deploy AI and GenAI solutions for business use cases.
  • Build and optimize LLM-based applications, AI agents, and multi-agent systems.
  • Develop RAG (Retrieval-Augmented Generation) solutions using enterprise data sources and knowledge repositories.
  • Integrate AI solutions with APIs, databases, business applications, and enterprise platforms.
  • Evaluate, fine-tune, and monitor AI models to ensure performance, accuracy, and reliability.
  • Implement Responsible AI, governance, security, and observability best practices.
  • Collaborate with Data Engineers, Data Scientists, and Product teams to operationalize AI solutions.
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