VP Engineering
il y a 17 heures
About Qevlar AI
Qevlar is a B2B SaaS scale-up on a mission to boost the productivity of cybersecurity teams with Artificial Intelligence. We build an AI platform that transitions Security Operations Centers from reactive to proactive units through autonomous security alert investigations.
In just two years, we have:
Raised a $14m initial round from EQT Ventures and Forgepoint Capital
Deployed our solution with major Enterprises such as Sodexo and GlobalConnect, and leading MSSPs like Orange Cyberdefense
Expanded to the US market with a growing North American presence
Ended 2025 with a strong multi-million dollar ARR and ambitious goals for 2026
We're looking for an experienced VP Engineering to scale our engineering organization and establish the systems needed to deliver predictably as we grow.
What will you doBuild and scale a high-performing engineering organisation while maintaining velocity
Establish processes and systems that enable predictable delivery without sacrificing speed
Define clear interfaces between engineering and other functions (Product, Sales, Customer Success)
Develop engineering managers and create clear career paths for the team
Own technical standards, delivery practices, and operational excellence
Partner with the CTO on technical strategy while owning day-to-day execution
Manage BYOC deployments and enterprise customer requirements while maintaining continuous deployment cadence
You have:
Significant engineering leadership experience with a track record of scaling teams through Series-B growth stages
A concrete system you've implemented before for predictable delivery - not theory, but something you've actually deployed and measured
Strong business acumen: you understand customer needs, revenue implications, and how engineering decisions impact the business
Track record of building engineering management layers and developing technical leaders
Experience balancing rapid iteration with enterprise stability requirements
Extreme ownership: you make autonomous decisions with data, then execute without needing constant validation
Customer-centric mindset with a bias toward shipping and iteration
Bonus points for:
Experience with AI/LLM-based products or infrastructure
Background in cybersecurity or highly regulated environments
Experience managing enterprise deployments in BYOC or multi-tenant environments
Strong architecture skills
Work on cutting-edge AI applied to a critical domain (cybersecurity)
Shape the engineering culture and systems of a fast-growing startup
Significant equity stake with real upside potential
High autonomy and direct impact on company trajectory
Paris-based with flexible remote work
Intro Call
Hiring Manager Interview
Case Study
Culture Fit
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