Tech Lead: Data Pipelines & AI Infra (Paris)

Arlq; Paris; Hybride; EUR 120 000 - 170 000; Plein temps

Avantages offerts par ce poste

Equity stake

Résumé du poste

Arlequin is building sovereign European AI infrastructure to process massive data with bias-free results. The Senior SWE will own large-scale data pipeline architecture, production AI infrastructure, and engineering standards, while mentoring the team.

Expect 50-70% hands-on coding and significant leadership across multiple projects in a fast-growing startup. The role requires 6+ years of SWE experience, mastery of TS/Node with Python data pipelines, and a strong preference for data-intensive,

Qualifications

• 6+ years of SWE experience
• 3+ years on complex or data-intensive architectures
• Mastery of a modern TypeScript/Node stack AND comfort with Python for data pipelines
• Expertise in data pipelines at scale, ML/AI in production, distributed systems, or frontend
• Ability to code AND guide a team technically through mentoring and setting standards
• Startup experience (Series A to B/C) is a plus
• Professional English proficiency

Responsabilités

• Own the most structuring technical initiatives: large-scale data pipelines and production AI infrastructure
• Code 50-70% of time in areas where senior technical judgment matters and mentor the team
• Guide the team through best practices, review processes and engineering standards
• Collaborate with Head of Engineering to absorb ambitious parallel projects
• Build scalable architecture patterns and contribute to monorepo scalability

Connaissances

SWE experience

Mentoring

Code review

Engineering standards

Distributed systems

Data pipelines

Outils

TypeScript/Node

Python

Docker

Description du poste

Arlequin is building sovereign European AI infrastructure to process massive data with bias-free results. The Senior SWE will own large-scale data pipeline architecture, production AI infrastructure, and engineering standards, while mentoring the team.

Expect 50-70% hands-on coding and significant leadership across multiple projects in a fast-growing startup. The role requires 6+ years of SWE experience, mastery of TS/Node with Python data pipelines, and a strong preference for data-intensive,