Tech Lead

Arlequin AI; Paris; On-site; EUR 80,000 - 100,000; Full time

Benefits offered by this job

80-100k+€ + BSPCE

On-site central Paris

Job summary

Arlequin AI is building a sovereign European AI platform to process massive data with bias-free results, with high-impact use cases like fighting disinformation. You will join to own key technical initiatives, including data pipeline architecture and production AI infrastructure, guiding a team, and mentoring engineers.

You’ll code 50–70% of your time and shape the engineering standards and long-term scalability as the company grows toward ambitious projects in parallel.

Qualifications

• 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

Responsibilities

• 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
• Code 50–70% of your time in areas where senior technical judgment makes the difference, and guide the rest of the team through expertise and mentoring
• Help relieve the Head of Engineering on complex initiatives and enable absorption of multiple ambitious projects in parallel
• Guide monorepo scalability and engineering standards
• Mentor team, perform code reviews, and help set engineering standards

Skills

SWE experience

TypeScript/Node

Python for data pipelines

Data pipelines at scale

Mentoring & code reviews

Startup experience (Series A–B/C)

Tools

Monorepo (Turbo)

React 19

Hono

Node 24

PostgreSQL

Drizzle

Docker

Job description

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).

~30 people, post-seed, Series A in progress. On-site in Paris.

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

• 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

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 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)

1. Screening (20 min)

2. Fit interview (45 min)

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

4. Culture fit with the founders (1h)

5. Ref calls

6. Offer

Package

• 80-100k+€ + BSPCE

• On-site central Paris