AI Security Specialist

Skills

About the Role

You will secure model training and serving infrastructure, build detection and guardrail systems, conduct adversarial testing, and drive fixes through completion. You will partner with engineering groups to establish secure defaults, threat-model AI features, and set the technical direction for AI security.

Requirements

• 8–10 years of security engineering experience, including hands-on work securing production ML systems or large-scale ML infrastructure
• Experience designing and shipping security systems and tooling
• Knowledge of cloud and infrastructure security, including IAM, Kubernetes, network segmentation, secrets management, and infrastructure as code
• Understanding of ML training and serving pipelines, model supply chain risks, and protection of model weights and artifacts
• Knowledge of LLM and generative AI attack vectors, OWASP Top 10 for LLMs, and MITRE ATLAS
• Coding skills in Python or Go
• Experience setting technical direction and influencing senior engineers and leaders without formal authority

Responsibilities

• Design and build security controls for model training and serving infrastructure
• Engineer detection, monitoring, and guardrail systems for model inputs, outputs, and agentic tool use
• Conduct adversarial testing and red-teaming across models, pipelines, and products
• Drive security fixes to completion
• Create secure defaults for model training, evaluation, and deployment
• Threat-model and review customer-facing AI features before launch
• Set AI security standards, reference architectures, and roadmap

Benefits

• Company equity package
• 401(k) with 3% employer match and Roth 401(k)
• Medical, dental, and vision insurance with PPO, HSA, and FSA options
• 11 paid holidays
• Unlimited PTO and sick time
• 16 weeks of paid parental leave
• Creative education stipend
• Commuter allowance
• In-office lunch five days per week