Lead SWE
Le poste
Preferred Experience
🔍 Who we're looking for
10+ years in software engineering, including 3+ years managing engineers (teams of 4-5 people or more, including senior profiles).
Strong back-end depth on data-intensive systems: Python or Rust in production, SQL, distributed pipelines, cloud infrastructure (GCP or equivalent).
AI-native way of building: you have been building with coding agents every day for months, and you know how to make a team ship faster and safer with them. At Ooak, every engineer runs several Claude Code sessions in parallel.
A track record of shipping in a demanding, fast-moving environment: start-up or scale-up.
High bar on quality and security: we handle our partners' most sensitive data.
Team first, low ego: you lead by clarity and trust, and you make the people around you better.
Fluent English, mandatory (working language with our clients and the labs).
The extras that make the difference
Experience with data engineering at scale: ETL/ELT, orchestration (Airflow, Dagster, etc), warehouses and lakes.
Experience with data anonymization, privacy, or security-sensitive systems.
Strong interest in AI, RL environments, and how frontier models are trained.
TypeScript on the side, for the platform.
🎁 Why join us
Entrepreneurial adventure: founding impact, live the early days of an ambitious company at the front line of the AI revolution.
Backed by Y Combinator, join just as we accelerate.
Offices in central Paris.
Perks: Alan health insurance (mutuelle), 50% Navigo covered.
Recruitment Process
✏️ Recruitment process
We move fast.
A 30 min intro call with Grégoire (co-founder)
A 60 min technical deep dive with Thomas (CTO & co-founder): your track record, technical judgment, how you lead
A technical case, presented to Thomas and a tech member
A final fit interview with 2 founders
Reference calls
Additional Information
- Contract Type: Full-Time
- Location: Paris
- Occasional remote authorized
- Salary: between 80000€ and 100000€ / year
Ooak data
Ooak Data construit Alexandria, une bibliothèque de jeux de données représentant des workflows réels d'entreprises. La société acquiert des environnements de données complets, les anonymise et les structure afin qu'ils puissent servir à l'entraînement et à l'évaluation des agents d'intelligence artificielle.
L'objectif est de confronter les agents à la complexité des outils, documents et processus réellement utilisés par les entreprises, au-delà des benchmarks académiques. Ces environnements sont destinés aux laboratoires d'IA qui développent des modèles capables d'accomplir des tâches professionnelles concrètes.
Équipe
5 personnes
Ville
Paris