GitGuardian is a global cybersecurity scale-up. The company is based in Paris, New-York City, Boston.
Among our early investors who saw our market value proposition, are the co-founder of GitHub, Scott Chacon, along with Solomon Hykes, Docker's co-founder. American and European top-tier VC firms have also invested in GitGuardian.
GitGuardian leads the way in Non-Human Identity security, offering end-to-end solutions from secrets detection in code, productivity tools and environments to strong remediation, observability and proactive prevention of leaks. Our solutions are already used by more than 600K developers worldwide!
We are building the AI operating model that empower 70+ engineers to ship faster without losing control of quality.
You will join our Developer Efficiency team and take ownership of one of the most ambitious projects we have in the company: moving our engineering processes and product development toward dark factury maturity, where AI handles the routine and humans focus on what requires judgment.
The objective is to design AI agents that code our products, build the specs-to-production pipeline that reduces lead time from idea to merge-ready code, and co-own the AI toolchain roadmap alongside our other Staff Engineers and CTO.
You will have a pragmatic view – based on your product-oriented mindset – on how this should be built. You will have the liberty and authority to define the approach and drive it forward. The tools you ship will be used every day by 70 engineers. You will spend your first weeks as part of feature teams to understand their actual constraints, then design and ship systems that make their daily work meaningfully better.
Your main responsibilities will be:
Design and ship AI agent workflows
Get an overview of our ongoing initiatives, challenge and improve them
Design and deploy background AI agents that autonomously handle specific engineering work: bug triage, diagnostics, patch suggestions, and code review
Define prescriptive agent workflows and skills that teams can adopt and extend
Improve our AI review pipeline
Own the specs-to-production pipeline
Implement automated workflows from design/spec to merge-ready code
Build faster feedback loops through better test generation and AI-assisted validation
Consolidate individual and team-level AI practices into a pragmatic, enforced approach: move from an artisanal one (Cursor + Claude Code per engineer) to a systematic one
Co-own the AI toolchain roadmap
Work directly with our Staff Engineers and CTO to define what gets built, in what order, and why
Join feature teams on a regular basis to keep the roadmap grounded in real constraints
If you think you match at least 70% of these criteria, please apply!
Here's what we consider essential for success in this role:
Founder or early-stage operator background: you have built and shipped an AI product, talked directly to users, and dealt with real constraints. You know what it's like to ship fast, with no safety net. If you founded a company (failed or not) and spent time in a startup accelerator, that background makes you stand out here.
Product mindset with technical depth: before shipping a feature, you ask who uses this and why. You treat internal engineers as customers and design solutions for their actual workflows.
Hands-on AI/LLM experience: you have developed with AI agents, LLM APIs (Claude, OpenAI, etc.), or agentic frameworks in production.
5+ years of technical experience, Python environments (our stack is Python + Django, TypeScript, Rust).
Influence without authority: you move people through ideas, prototypes, and clear thinking. You manage to build your solutions with a great balance between the vision of the Company and the needs of the teams.
Structured, autonomous execution: you can research a problem space, propose an opinionated solution, document it clearly, and drive it to completion with minimal oversight.
Fluency in English, written and spoken.
The following skills would strengthen your application but aren't required:
Background in platform engineering or developer tooling
Familiarity with CI/CD optimization
Basic knowledge of DORA metrics or DX Framework
Fluency in French
At GitGuardian, we are committed to building a diverse, equitable and inclusive workforce.
We will ask for your gender identity on the application page to help us understand the diversity of our applicant pool and to track our progress in attracting and hiring a diverse workforce. The information is optional and will not be disclosed to the hiring manager or the interview team and will not be considered in the hiring process. We appreciate your willingness to share this with us so that we can continue to improve our diversity, equity and inclusion efforts.
1. Video call with a Talent Acquisition team member
To discover your professional project and evaluate if there could be a mutual match.
2. Team interview / Interview with your future manager
To know more about yourself and your achievements, and present to you the team.
3. Technical interview
To evaluate your skills for the position and project yourself into the role.
4.1 Final interview with an Executive Manager
To detail our company’s vision and ambitions for the next couple of years.
4.2 References check
You can start thinking about two contacts who can attest to your previous or current professional experiences. These contacts should be as recent as possible, and we will call them at the end of the process.
Package that includes BSPCE
Lunch voucher (Swile, 9€ at 50%)
Sponsored Wellpass (gymlib)
Non-charged health insurance for children (Sidecare / Generali)
Up to €300 to improve your home office set-up
Yearly holiday allowance
Referral bonus of 4000€ for any new Guardian we might hire thanks to you
Team building: monthly budget dedicated to each employee that you can spend as you wish, with colleagues (latest examples to date: Michelin star restaurant, karaoke, stand-up show, kitesurfing week-end, ...)
And also...
