Security Engineer (Detection and Response) in London

Requirements:

• 3-5+ years in security operations, detection engineering, or incident response with a proven track record of identifying and stopping sophisticated attacks in production environments.
• 3+ years specifically securing AI/ML infrastructure, high-performance computing environments, or other distributed systems at scale.
• Strong programming skills in Python, KQL, SPL, or similar languages that allow you to build custom detection logic, automate response workflows, and create tools that operationalize security at scale across cloud-native and distributed computing environments.
• Experience with SIEM platforms, detection technologies, and forensic investigation techniques with demonstrated ability to build detection for novel attack techniques that don't have established patterns yet and to conduct forensics in complex distributed environments.
• Self-directed execution mindset with a track record of securing high-value intellectual property, automating incident response in complex environments, and identifying critical security gaps through proactive threat hunting before they become incidents.
• Deep alignment with WRITER's values – you naturally connect across security, infrastructure, and AI research teams to build comprehensive defenses, challenge assumptions about what's possible in AI security engineering, and own the protection of our AI platform with unwavering accountability and a commitment to staying ahead of evolving threats.

What the job involves:

• Join WRITER's security team as a staff detection and response engineer and help protect the AI infrastructure that's transforming how the world works.
• Build sophisticated detection systems that identify attacks targeting our AI platform, training data, and model deployments while creating automated response capabilities that scale with our explosive growth.
• This isn't just traditional security work – you're defending cutting-edge AI/AGI systems against adversaries who are evolving their tactics as fast as AI itself advances.
• This role combines hands-on security engineering with strategic thinking to stay ahead of novel threats that don't exist in textbooks yet.
• Be the operational arm of our security function, translating threat intelligence into real-time detections, coordinating incident response across multiple teams, and hunting for sophisticated attacks across GPU clusters and distributed training environments.
• If you're excited by the challenge of securing systems that are fundamentally different from anything you've protected before, this is your opportunity to define what AI security engineering looks like at scale.
• Work closely with our AI Security research team, Cloud Infrastructure, Software Security Engineering, and AI researchers to build a defence-in-depth strategy that protects one of the most valuable AI platforms in the industry.
• The threats are real, the stakes are high, and the problems are intellectually fascinating.
• This role can be based in San reporting to our head of security operations.
• Design and implement detection strategies that identify AI-specific threats including prompt injection, model extraction, data poisoning, adversarial examples, and unauthorized access to training datasets or model weights across our distributed infrastructure.
• Build automated response playbooks and orchestration workflows that contain threats without human intervention, creating self-healing security systems that reduce mean time to response from hours to minutes while automatically remediating compromised inference endpoints.
• Lead security incident response coordination across all teams (Cloud, AppSec, Enterprise, AI Security) when AI infrastructure or models are compromised, conducting forensic investigations on training pipeline attacks and model manipulation attempts while drafting clear incident communications for engineering and executive leadership.
• Hunt proactively for sophisticated threats across GPU clusters and training infrastructure by analyzing model outputs for signs of compromise, reproducing AI-specific vulnerabilities from security research, and identifying visibility gaps in distributed training environments before adversaries exploit them.
• Build detection-as-code frameworks with version control and automated deployment, onboard telemetry from AI training infrastructure and inference endpoints, and create dashboards that track model security metrics, GPU utilization patterns, and access to sensitive research data.
• Collaborate cross-functionally as the operational security partner for all teams – translating AI Security's threat research into production detections, monitoring Cloud Infrastructure's GPU clusters for threats, detecting customer-impacting incidents for Software Security Engineering, and enabling responsible AI development through security guardrails.
• Maintain 24/7 on-call rotation for critical AI security incidents, responding to real-time threats targeting our platform while continuously improving detection coverage and automation capabilities as our AI systems evolve.