About
This is an early-stage VC-backed startup in Paris, building the infrastructure layer that allows AI to reason across entire enterprise systems.
Their system maps decades of code, data, and business logic into a unified knowledge graph – so AI agents can understand, navigate, and transform these systems autonomously.
$6M seed closed (tier-1 VCs), first enterprise clients signed, four engineers already in place.
The team is small, technical, and moving fast. This is a true founding-stage environment.
What you'll do
- Design and implement the core enterprise knowledge graph connecting data, codebases, and business processes
- Architect systems that integrate heterogeneous enterprise applications into a unified control layer
- Build GenAI-powered workflows that operate on top of this ontology
- Turn forward-deployed prototypes into reusable, scalable product components
- Develop robust evaluation frameworks and infrastructure to ensure reliability at enterprise scale
- Design secure deployments, including on-prem environments with strict compliance requirements
What you'll need
- Strong academic background from a top-tier engineering school
- Excellent programming skills in Python, Java, or Go with strong system design fundamentals
- Experience modelling complex systems (schemas, ontologies, metadata layers, knowledge graphs)
- Practical experience integrating LLMs or GenAI workflows into production systems (RAG, embeddings, prompt design)
- Comfort translating ambiguous strategic vision into concrete technical architecture
- Bias for action and full end-to-end ownership
Shortlisted candidates will be contacted within 48 hours.
