Security Engineer, Detection and Response (us)

Writer · AI Frontier · San Francisco, CA · Engineering, product & design

Security engineer focused on detection and response for AI infrastructure, including AI-specific threats, automated response, and incident coordination across GPU clusters and training environments. The role involves building detection systems, automated response playbooks, and proactive threat hunting within a rapidly evolving AI security landscape.

What you'd actually do

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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

Skills

Required

  • 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, 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

Nice to have

  • Deep alignment with WRITER's values – you naturally Connect across security, infrastructure, and AI research teams to build comprehensive defenses, you Challenge assumptions about what's possible in AI security engineering, and you Own the protection of our AI platform with unwavering accountability and a commitment to staying ahead of evolving threats

What the JD emphasized

  • AI-specific threats
  • automated response
  • GPU clusters
  • distributed training environments
  • novel threats
  • sophisticated attacks
  • AI Security research team
  • AI platform
  • AI security engineering
  • AI infrastructure
  • AI/ML infrastructure
  • distributed systems at scale
  • automating incident response
  • proactive threat hunting

Other signals

  • AI-specific threats
  • automated response capabilities
  • GPU clusters and distributed training environments
  • novel threats