Cybersecurity Engineer – AI Risk and Governance

Role Overview

• Perform technical security testing and reviews of AI‑enabled applications, agents, and workflows
• Implement approved security architecture patterns for AI, ML, and LLM systems across cloud, hybrid, on‑prem, and OT‑adjacent environments
• Engineer secure inference paths, APIs, service identities, authentication flows, and segmentation boundaries aligned with least privilege and zero trust principles
• Implement technical safeguards to mitigate prompt injection, unauthorized context expansion, data leakage, hallucination risk, and unsafe output handling
• Configure and maintain controls for limiting, monitoring, logging, and managing AI usage across platforms, models, and agents
• Implement and validate technical controls supporting model explainability, traceability, and output validation where AI impacts operational, workforce, safety, or compliance decisions
• Review and validate LLM usage patterns, including prompt design, retrieval‑augmented generation (RAG), context window constraints, and output handling mechanisms
• Implement controls preventing unauthorized external model training, reuse, or retention of enterprise data by third‑party AI platforms
• Validate encryption, access logging, retention, and deletion controls for data ingested, processed, or generated by AI systems
• Execute AI‑specific threat modeling activities and contribute findings to enterprise and OT cybersecurity risk assessments
• Ensure AI systems produce security telemetry, logs, and audit trails sufficient to detect misuse, drift, policy violations, or anomalous behavior
• Integrate AI security signals into SOC, SIEM, and incident response tooling and workflows
• Support investigation and response to AI‑related incidents, including data exposure, model failure, unsafe outputs, or control breakdowns
• Conduct technical security reviews of vendor‑provided and embedded AI capabilities, assessing model behavior, data handling, and control alignment
• Enforce approved security requirements for AI vendors and prevent activation of AI features without required security validation and governance approval
• Drive alignment with ISO 42001 and related AI governance standards across applicable teams

Requirements

• Bachelor’s degree in Cybersecurity, Computer Science, Data Science, Engineering, or related field, or equivalent experience
• Minimum 5+ years of experience in cybersecurity, security architecture, or risk engineering roles
• Hands‑on experience securing data pipelines, APIs, cloud platforms, and analytics or ML‑enabled systems
• Strong understanding of identity, access management, encryption, logging, and secure system design
• Direct experience securing AI/ML platforms, LLMs, or analytics pipelines (preferred)
• Experience with cloud security (Azure, AWS, GCP) and SaaS‑based AI platforms (preferred)
• Familiarity with OT, critical infrastructure, or safety‑critical environments (preferred)
• Security certifications such as Security+, SecurityAU+, CISM, or cloud security certifications (preferred)

Tech Stack

• AWS
• Azure
• Cloud
• Cyber Security
• Google Cloud Platform

Benefits

• medical, dental, and vision coverage
• life and AD&D insurance
• short and long-term disability coverage
• paid time off
• employee assistance program
• participation in a 401k program that includes company match
• additional voluntary benefits