Cybersecurity Full Stack AI Engineer
- london, england, United Kingdom
- Permanent·On-site
- Full time
- £80 - £120 Per Hour
Job Description
This cybersecurity startup is building AI-powered threat detection that actually works. While legacy security tools drown analysts in false positives, their platform uses machine learning to identify real threats with precision — from insider threats to zero-day exploits to nation-state attacks. Their customers include FTSE 100 companies and critical national infrastructure. They've just raised Series A funding and are scaling the engineering team. They need a Full Stack AI Engineer who can build across the entire product — from the security analyst dashboards to the ML models that power detection, to the data ingestion pipelines that process billions of events daily. Security is a domain where AI genuinely matters. The attackers are using it, and the defenders need to as well. You'll work on anomaly detection, behavioural analysis, natural language processing for threat intelligence, and building interfaces that help analysts respond faster. The problems are adversarial, the data is noisy, and the stakes are real.
Responsibilities
- Build analyst-facing interfaces for investigating and responding to security threats
- Design and implement ML models for anomaly detection, behavioural analysis, and threat classification
- Create data pipelines that ingest and process security telemetry at massive scale
- Build APIs and backend systems that serve ML insights in real-time
- Work with security researchers to translate threat intelligence into detection capabilities
- Ship features that help analysts cut through noise and focus on what matters
Qualifications
- A full-stack engineer with experience building production AI systems
- Comfortable across React/TypeScript frontends and Python/Go backends
- Hands‑on experience with ML — anomaly detection, classification, or NLP
- Interest in cybersecurity — you don't need to be an expert, but you should be curious
- Experience with high-volume data pipelines and streaming systems
- Thrive in fast-paced environments where you ship quickly and iterate