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Talan

Agile IT transformation consulting and delivery

Data & GenAI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNantes, France

About the Job

Requirements

  • Have a higher education background in computer science, data science, artificial intelligence, or a related field.
  • Have at least 4 years of experience developing AI solutions, in data engineering, or in machine learning.
  • Have strong knowledge of data processing, data utilization, and the industrialization of AI solutions.
  • Have strong command of Python and its data and AI ecosystem.
  • Understand modern data architectures and data governance principles.
  • Have experience with generative AI solutions, including large language models, retrieval-augmented generation, or AI agents.
  • Have command of SQL and NoSQL databases.
  • Have experience with cloud platforms such as Azure, AWS, GCP, or Scaleway.
  • Know DataOps, MLOps, and LLMOps practices.
  • Have command of version-control and continuous-integration tools such as Git, GitLab CI/CD, or Azure DevOps.
  • Know containerization and orchestration tools such as Docker and Kubernetes.
  • Understand distributed architectures and data-processing pipelines.

Responsibilities

  • Design and develop AI assistants and conversational systems that use enterprise data.
  • Build performant retrieval-augmented generation architectures that enrich models with business knowledge.
  • Design autonomous AI agents capable of interacting with information systems and data platforms.
  • Integrate, orchestrate, and optimize proprietary and open-source models.
  • Implement document retrieval, reasoning, and data-based action-execution solutions.
  • Improve answer relevance through prompt engineering, retrieval, and evaluation mechanisms.
  • Design robust, scalable, and secure data and AI architectures.
  • Develop industrialized AI services, APIs, and components.
  • Integrate AI solutions into clients’ data ecosystems.
  • Work with data engineering teams to prepare, qualify, and expose data.
  • Contribute to technology foundations that accelerate development of data and AI use cases.
  • Implement DataOps, MLOps, and LLMOps practices to ensure production solutions are reliable.
  • Design, train, and deploy machine-learning models when needed.
  • Conduct exploratory analyses and advanced experiments using structured and unstructured data.
  • Evaluate and optimize AI model performance.
  • Develop explainability, responsible AI, and model-governance approaches.
  • Collaborate with business teams to turn data into decision-making and performance drivers.
  • Define quality and performance indicators for data and AI solutions.
  • Implement monitoring, traceability, and observability mechanisms for AI models and agents.
  • Monitor the ongoing performance of retrieval-augmented generation architectures, multi-agent systems, and machine-learning models.
  • Evaluate generated-answer quality and drive continuous improvement.
  • Ensure compliance, security, and governance of data used by AI solutions.

Desired Qualifications

  • Experience with one or more of the following: Modern Data Platform, Microsoft Fabric, Databricks, Snowflake, Azure AI Services, OpenAI, or Azure OpenAI.

About the Company

Talan

Agile IT transformation consulting and delivery

Talan is a European consulting and IT services group that helps organizations transform and adapt to fast-changing environments. It offers a full range of services from strategic business consultancy to packaged IT solutions, including production support, software development, business analysis, and nearshore delivery. The company works by deploying multidisciplinary teams across its global offices to guide clients through agile transformations, change programs, and IT modernization. Talan differentiates itself through its international footprint, sector focus on Major Service Operators, and a culture built on transparency, respect, teamwork, entrepreneurial spirit, and commitment. With strong organic growth and a large pool of over 3,500 consultants, its goal is to create and share value for clients while coaching and developing its people—empowering customers to transform and compete more effectively.

Company size
1,001-5,000
Company stage
Late Stage VC
Total funding
$110M
Headquarters
Paris, France
Founded
2002

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