AI Engineer - Rag & Agentic & Knowledge Graph - Freelance

Taux journalier (TJM): 550

AI Engineer — Python, Agentic AI & Knowledge Graphs

Context

Our client, a SaaS software company operating internationally, is looking for an AI Engineer to strengthen its AI Engineering team.

Reporting to the Head of Data & AI, you will help build AI features embedded in the platform, deployed in both SaaS and on-premise environments.

We are looking for a Python backend developer who has delivered AI agents in production, with expertise in ontologies and knowledge graphs — a core requirement for this role.

Responsibilities

• Design and develop backend components for AI features running in production.

• Build AI agents, including multi-agent systems, workflow orchestration and LLM-driven reasoning.

• Develop MCP servers and custom tools connecting agents to applications, APIs and databases.

• Design RAG and agentic architectures combining vector search, knowledge graphs and ontologies.

• Model business domain knowledge to support agent capabilities and semantic reasoning.

• Set up an AI gateway such as LiteLLM for model routing, governance and cost control.

• Implement observability and evaluation for AI services.

• Mentor junior developers and contribute to AI engineering best practices.

Must-have skills

• Python / FastAPI: expert-level backend development, REST APIs, microservices and asynchronous programming.

• Generative AI in production: significant, proven experience beyond POCs.

• Agentic AI: LangChain, LangGraph or equivalent, and multi-agent systems.

• MCP and A2A: Model Context Protocol and Agent-to-Agent protocols.

• RAG: vector search, embeddings and context optimization.

• Ontologies and knowledge graphs: business domain modeling and semantic reasoning.

• Production engineering: OpenTelemetry, Docker, CI/CD, Git and testing with pytest.

• Databases: SQL, particularly SQL Server and MySQL, and vector search using Elasticsearch or equivalent.

Nice to have

• Neo4j or another graph database — strongly preferred.

• LiteLLM or another LLM gateway.

• LangSmith, Langfuse or Arize Phoenix.

• Google Cloud and GKE.

Profile

• Senior backend developer with practical expertise in agentic AI.

• Autonomous, pragmatic and able to contribute quickly.

• Strong communicator, comfortable working in English with international teams.

• Able to mentor junior developers and share engineering best practices.

Practical information

• Start date: ASAP.

• Duration: 3 months, renewable.

• Location: Paris, with 1/2 days on-site per week.

• Languages: French and English.