Tech Lead

Il y a 3 jours

Paris, Île-de-France Arlq Temps plein

Own the most structuring technical initiatives: large-scale data pipelines, production AI infrastructure and engineering standards.



Si vous souhaitez postuler à cet emploi, veuillez vous assurer que vous remplissez les conditions suivantes, énumérées ci-dessous.

6+ years of experience


Full-time


On-site in Paris


About Arlequin

Arlequin is building the sovereign European alternative to Palantir: an AI platform capable of processing massive data volumes without bias, with high-impact use cases such as fighting disinformation. Founded in late 2024 by Hugo Micheron (researcher in geopolitics and systemic risk) and Antoine Jardin (CNRS research engineer).


The role

You'll join Arlequin to own, alongside the Head of Engineering, the most structuring technical initiatives: large-scale data pipeline architecture, production AI infrastructure, integration of unsupervised models on massive datasets, monorepo scalability and engineering standards. You'll code 50-70% of your time on the areas where senior technical judgment makes the difference, and guide the rest of the team through expertise and mentoring.


This role was created both to relieve the Head of Engineering on the most complex initiatives and to bring the level of seniority that will unlock Arlequin's ability to absorb several ambitious projects in parallel.


Stack

AI pipelines: Python, unsupervised models on massive multilingual datasets


Advanced patterns: end-to-end Zod schemas, Vanilla Extract for styling


Quality & ops: strict TypeScript, Docker


What we're looking for

6+ years of SWE experience, including at least 3 on complex or data-intensive architectures


Mastery of a modern TypeScript/Node stack AND comfort with Python for data pipelines


At least one area of excellence among: data pipelines at scale, ML/AI in production, distributed systems, or frontend


Ability to code AND guide a team technically - you make the difference by example, not by hierarchy


A real appetite for mentoring, code review and setting engineering xuezdbg standards


Ideally Series A to B/C startup experience


Professional English


Bonus

Data-intensive B2B SaaS products


Interest and ability to work alongside researchers in ML/AI (Phd/PostDoc/Senior)


Ability to handle and interact with HPC platforms, massively parallel compute stack


Process (~2-3 weeks)

Screening (20 min)


Fit interview (45 min)


Async technical case study (3-4h max) + 1h debrief


Culture fit with the founders (1h)


Ref calls


Offer


Package

Competitive compensation including equity stake


On-site central Paris