Tech Lead

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ENGINEERING

Tech Lead

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

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).

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

Platform: monorepo TypeScript (-Turbo), React 19, Hono, Node 24

Data & infra: PostgreSQL + Drizzle, Scaleway

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

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 standards

Ideally Series A to B/C startup experience

Professional English

Bonus

Monorepo experience (Turbo, Nx, Bazel)

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