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Onepoint

End-to-end organizational transformation and modernization

AI Engineer

AI Application EngineeringUpdated on Nov 15
Full-timeParis, FranceNo salary listed

About the Job

Requirements

  • At least two years of experience in Data Science, Data Engineering, or Software Engineering, with initial concrete generative AI achievements through professional projects or advanced personal projects.
  • Ability to adapt across client technology environments and constraints, including legacy systems and banking security.
  • Ability to explain complex technical concepts to nontechnical business leaders.
  • Ability to produce clean, maintainable code.
  • Indispensable proficiency in Python and software engineering practices, including Clean Code, Git, and continuous integration and continuous delivery.
  • Ability to orchestrate complex chains using tools such as LangChain, LlamaIndex, and Semantic Kernel, and choose suitable models, including OpenAI, Azure AI, Bedrock, Vertex AI, Mistral, or Llama.
  • Ability to integrate solutions into client data ecosystems, using technologies such as Pinecone, Qdrant, Weaviate, pgvector, or Elasticsearch.
  • Ability to deploy on AWS, Azure, GCP, or constrained on-premise environments.
  • Ability to implement client-appropriate monitoring and evaluation tools for LLM operations, such as LangSmith, MLflow, or Ragas.

Responsibilities

  • Implement retrieval-augmented generation solutions, AI agents, and business assistants.
  • Integrate large language models into existing systems and orchestrate their interactions.
  • Optimize prompts, embeddings, and orchestration chains to improve relevance and performance.
  • Manage cost, latency, and security concerns for generative AI solutions.
  • Establish governance and compliance practices for generative AI.
  • Collaborate with Data, IT, and business teams to ensure solution consistency.
  • Analyze business needs and define the appropriate strategy, such as retrieval-augmented generation, agents, or fine-tuning, and select a technology stack suited to the client environment.
  • Develop robust, modular Python code to integrate large language models with existing information systems, APIs, and data lakes, moving solutions beyond proof-of-concept.
  • Control costs and latency through LLM operations and implement security guardrails.
  • Explain technical concepts and guide client business and IT teams in adopting these technologies.

About the Company

Onepoint

End-to-end organizational transformation and modernization

Onepoint helps organizations modernize and transform by providing end-to-end advisory and delivery services that cover strategy, design, platforms, and implementation for both private sector companies and public administrations. It works by organizing its experts into open communities to combine business and technology skills, guiding projects from strategic vision through operational deployment across its global network of offices. The company differentiates itself through its open-community model, audacious and practical mindset, and its focus on designing concrete paths to the future—new ways of working, new business models, and new places—rather than just delivering isolated tech solutions. Its goal is to design a new world for its clients and help them move Beyond the obvious.

Company size
1,001-5,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$176M
Headquarters
Paris, France
Founded
2002

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