Job Title
Full Stack Engineer
Salary
£120k-£130k + Equity
Company Description
Aisy.ai is a $2.3M seed‑funded cybersecurity startup building an AI‑native vulnerability management engine. Founded by the former head of Hacker R&D at HackerOne, the team is backed by 6 Degrees Capital, Flying Fish Ventures, Osney Capital, and angel investors from DeepMind, Cisco, and 1Password.
Job Description
Join Aisy.ai as a Full Stack Engineer to build an AI‑driven platform that prioritizes cybersecurity threats using real‑world attacker logic. You will work directly with the founder to develop Python backends, React frontends, and core ML systems, transforming how organizations manage vulnerabilities by focusing on exploitable attack paths rather than noise.
Location
London, UK
Why this role is remarkable
- Work directly alongside founder Shlomie Liberow, a world‑class security expert who led Hacker R&D for HackerOne and managed programs for the UK Ministry of Defence.
- Join a small, high‑impact team of four as an early employee, gaining massive ownership over a product targeting a $17B+ market with unique AI‑native technology.
- Engage in deep technical challenges across the stack, from building autonomous agentic AI features and ML evaluation pipelines to designing complex authorization logic for enterprise customers.
What You Will Do
- Develop and scale end‑to‑end features using a Python and Prefect backend coupled with a modern React frontend to deliver actionable security insights.
- Own the core ML lifecycle, including model training, evaluation pipelines, and the implementation of agentic AI features that simulate real‑world attacker perspectives.
- Collaborate closely with customers to rapidly prototype, build, and ship features that address critical pain points in how organizations defend against complex vulnerability chains.
The ideal candidate
- Has 2‑6 years of professional full‑stack experience with strong engineering fundamentals in Python and modern frontend frameworks like React.
- Possesses genuine depth in Machine Learning, understanding model training and evaluation techniques beyond simple API consumption to build robust AI‑native products.
- Thrives in fast‑paced startup environments, demonstrating curiosity, a builder’s mindset, and the ability to ship high‑quality code that solves real‑world customer problems.
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