Quick Overview
Job Description
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 three years, we have:
Raised a total of $44m in series-A & seed rounds from EQT Ventures, Forgepoint Capital and Partech
Deployed our solution with major Enterprises such as Sodexo and GlobalConnect, and leading MSSPs like Orange Cyberdefense
Grown to 1,500+ clients across the US and EMEA
Ended 2025 with a strong multi-million dollar ARR, and we're targeting $25M by the end of 2027
We are hiring a Senior Product Manager to own a core area of the Qevlar platform, spanning investigations, threat detection and response.
You will work directly with the VP Product and lead a dedicated squad of engineers, with real ownership of the problems you pick up and the results you deliver.
This is a role for someone who knows security operations from the inside.
You have built product for the people who write detections, triage alerts or manage vulnerabilities, and you understand how a SOC actually runs. You will spend your time with analysts, SOC managers and CISOs, shaping how AI does their work with them, and you will ship product that changes how they operate.
What you will actually do
Own the roadmap for your area: discovery with customers and prospects, opportunity framing, requirements, prioritisation and delivery, with a squad of engineers and an engineering manager alongside you.
Spend time with SOC teams at enterprises and MSSPs to understand how they detect, investigate and respond today, and translate that into product that fits their workflow rather than adding to it.
Define what good looks like for an AI driven security product: how we measure the quality of an investigation or a recommendation, how we show our reasoning, and how we earn the trust that lets a team act on what Qevlar tells them.
Partner with engineering, customer success and sales to take features from idea to production and into the hands of customers, and follow through on adoption and impact.
Bring the market in. You will track the detection, security orchestration and vulnerability management landscape and know where Qevlar can win.
What we're looking for
At least 5 years of product management experience on a security product: a detection platform (SIEM, XDR, detection engineering or content) or a vulnerability management platform.
A working understanding of security operations. You know how detections are written and tuned, how alerts flow through a SOC, and how vulnerabilities get prioritised and fixed, because you have shipped product into those workflows.
A track record of taking products from discovery to launch in a B2B SaaS environment, and of making prioritisation calls with customers, revenue and engineering capacity all in view.
An AI native way of working. You use AI tools every day to research, analyse, prototype and write, you understand how large language models behave in production, and you have shipped or built with them.
Comfort with an early stage company: ambiguity, pace, and problems nobody has solved yet.
At least C1/C2 level in English. We are a distributed team and most decisions are made in writing.
Why join us
Work alongside senior leadership to define platform strategy for a fast-growing cybersecurity startup
Direct impact on enterprise revenue and global expansion
Work with world-class engineers on complex infrastructure challenges with real-world impact in cybersecurity
Excellent career opportunities in a rapidly scaling business
A company culture that values autonomy and creativity
Opportunity for equity and early ownership
We’re flexible on location.
If you’re excited about helping security teams adopt cutting-edge AI, we’d love to hear from you. Let’s build the future of cybersecurity together!
Hiring process
Recruiter Call: Initial conversation about your background, the role, and mutual fit.
Head of Product: Deep dive on product thinking, technical approach, and past platform work.
Product Case Study: Work through a realistic platform prioritisation challenge. Assess how you balance competing demands and communicate trade-offs.
Culture fit: Strategic alignment, vision for platform products, and your career goals.