AI Cyber Principal

The Charles Stark Draper Laboratory•Cambridge, MA

6d•Onsite

About The Position

The AI Cyber Principal is responsible for enabling the cyber security, resiliency and monitoring of the internal Artificial Intelligence models, efforts and systems by establishing a framework that enables AI-driven tools into all applicable workflows. They are responsible for protecting against AI-specific threats, establishing model governance, and automating defense capabilities. The incumbent is instrumental in securing the deploying and extending AI capabilities at Draper, with an understanding of AI and cyber security threats.

Requirements

Hands-on experience securing Machine Learning pipelines, data platforms, and containerized/microservices architectures.
A strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI.
Proficiency in coding languages like Python, as well as IaC (Infrastructure as Code) tools like Terraform.
Proven ability to manage teams, work with executive stakeholders, and translate complex security concepts into business requirements
7 years in cybersecurity, cloud security (AWS, Azure, GCP), or security engineering.
Demonstrated experience in applying AI Risk Mitigations and Monitoring frameworks.
Applicants selected for this position will be required to obtain and maintain a US government security clearance. Active Top Secret Clearance with SCI eligibility is required.

Nice To Haves

master’s degree preferred

Responsibilities

Lead cross-functional initiatives to use AI and Large Language Models (LLMs) to enhance incident response, alert triage, threat hunting, and automated remediation
Design security controls for AI/ML environments, protecting pipelines against model theft, data poisoning, and adversarial attacks
Develop and enforce policies and governance frameworks regarding responsible AI usage, compliance, and emerging AI regulations.
Anticipate threats by simulating AI-assisted attacks and architecting predictive defensive measures
Partner with DevOps, data engineering, and AI/ML teams to bake "security by design" into all AI pipelines and products
Establish metrics to monitor the security of AI applications across the full life cycle and establish AI cyber governance framework that aligns emerging federal AI security and assurance expectations.