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Capgemini

Global consulting, technology services, outsourcing

AI / Data Engineer Intern

AI Application Engineering +1Updated on Nov 14
InternshipIssy-les-Moulineaux, FranceNo salary listedIn-person

About the Job

Requirements

  • Be in the final year of an engineering-school program or a master's (bac+5) program in computer science, data science, or artificial intelligence.
  • Have solid theoretical knowledge of data processing, data storage (databases, data lakes, and data warehouses), and data transport (batch and streaming).
  • Be able to develop in Python and deliver clean, documented, testable, and maintainable code.
  • Have introductory knowledge of large language models and generative AI, including prompt engineering, embeddings, retrieval-augmented generation, and agent orchestration concepts, gained through an academic, personal, or internship project.
  • Be bilingual in English and French and be mobile.
  • Have analytical skills and a critical approach to model outputs, and be willing to experiment rigorously.

Responsibilities

  • Contribute to a research and development project led by the Capgemini Invent Lab and participate in Data Engineering and generative AI/agentic engineering consulting assignments for Capgemini Invent clients.
  • Build data pipelines for collecting, organizing, and modeling high-volume data, enabling use by analysts and data scientists and supporting generative AI use cases, including document ingestion and parsing, chunking, embedding generation, and vector database indexing.
  • Deploy complex infrastructure on cloud providers or on-premises using infrastructure-as-code and continuous integration and deployment tools.
  • Deploy data and AI stacks, including raw and structured data storage, model-serving components, an LLM gateway, and agent orchestration.
  • Design and industrialize applications based on large language models, retrieval-augmented generation and advanced retrieval-augmented generation architectures, agent and multi-agent orchestration using LangGraph, agent tooling, and context and memory management; select and compare models based on cost, latency, and data sovereignty constraints.
  • Build evaluation datasets and metrics for relevance, hallucinations, cost, and latency; implement tracing and production monitoring; and implement safeguards for industrial use, including security, confidentiality, and AI Act compliance.
  • Design, develop, and containerize back-end applications and REST APIs incorporating data, AI, or LLM agents for production use by end users or other application services.
  • Design complete data and AI architectures addressing security, scalability, auditability, and availability, and integrate generative AI components such as LLM gateways, retrieval-augmented generation, and agents into existing client information systems.
  • Participate in technology monitoring, particularly for generative AI and agentic technologies, and share technological expertise to improve practices and develop solutions for clients.

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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