AI Security Specialist

What you'll do

• Build security controls for model training and serving infrastructure, pipelines, compute, artifacts, and software supply chains.
• Develop production detection, monitoring, and guardrails; conduct adversarial testing and drive remediation.
• Partner with ML, platform, and product teams to establish secure defaults, review AI features, and set AI security standards and roadmap.

What they ask for

• 8–10 years in security engineering, including hands-on experience securing production ML systems or large-scale ML infrastructure.
• Track record designing and shipping security systems and tooling.
• Deep cloud and infrastructure security knowledge, including IAM, Kubernetes, network segmentation, secrets management, and infrastructure as code; strong understanding of ML pipelines, attack surfaces, and model supply chain risks.
• Fluency with LLM and generative AI attack vectors and frameworks such as OWASP Top 10 for LLMs and MITRE ATLAS; strong coding skills in Python or Go.

Nice to have

• Experience at a foundational model company or AI research lab; securing GPU compute environments or distributed training at scale.
• Hands-on use of adversarial testing tools such as Garak or PyRIT; experience securing audio, media, or other generative content pipelines.

Pay

$276,960 - $363,510 USD base salary

Tools

IAM, Kubernetes, infrastructure as code, OWASP Top 10 for LLMs, MITRE ATLAS, Python, Go, Garak

AI focus

Secures AI models across training, evaluation, serving, and product deployment, including model supply chains, LLM and generative AI attack vectors, guardrails, and adversarial testing.