Senior AI Security Engineer

enGen is a company focused on securing AI/ML and Generative AI systems in a regulated healthcare environment. The Senior AI Security Engineer will design, implement, and operate security controls for these systems while advising on emerging AI threats and regulatory exposure.

Responsibilities:

• Design, implement, and operate security controls for AI/ML, GenAI, and agentic systems — spanning model-level, data-level, and platform-level protections across Azure, GCP, AWS, and SaaS
• Engineer and enforce guardrails that mitigate prompt injection, unsafe outputs, unauthorized tool execution, data leakage, and insecure agentic workflow behavior, with explicit focus on PHI/PII exposure
• Design and execute AI red-team exercises targeting LLMs and AI agents including prompt injection (direct and indirect), jailbreaking, tool and memory poisoning, behavioral drift, unsafe autonomy, and emergent privilege escalation
• Analyze agent logic, tool graphs, and multi-step workflows to identify systemic security weaknesses beyond prompt-level attacks; translate findings into reusable attack libraries and actionable engineering fixes
• Build and maintain monitoring, logging, and alerting for AI systems covering prompt behavior, tool invocation patterns, output anomalies, and workflow execution — and implement detection content for policy-violating AI behavior
• Embed security controls into CI/CD pipelines and agentic delivery workflows; partner with AI platform, data engineering, and application teams to integrate security requirements from design through deployment gate
• Apply NIST AI RMF, MITRE ATLAS, and OWASP LLM Top 10 to assess and manage AI security risks; contribute to enterprise AI security standards, reference architectures, and governance policy; advise leadership on AI cybersecurity risk and regulatory considerations specific to healthcare AI deployment
• Other duties as assigned or requested

Requirements:

• 5 years of experience in Cybersecurity engineering, application security, or platform security
• 3 years of experience in AI/ML or Generative AI security (prompt injection defense, unsafe output handling, tool-use abuse, data leakage)
• Bachelor's degree in Computer Science, Computer Engineering, Information Technology, Cybersecurity, or closely related discipline or relevant experience and/or education as determined by the company in lieu of bachelor's degree
• 5 years of experience in Securing production systems in enterprise environments
• 3 years of experience in Hybrid multi-cloud security (Azure, GCP, AWS)
• 2 years of experience in Detection engineering, monitoring, and alerting for complex application or workflow environments
• 2 years of experience in AI red-team execution (jailbreaking, behavioral drift, misuse-case validation; tools such as PyRIT, Promptfoo, AgentDojo)
• 2 years of experience in Securing agentic systems, multi-step AI workflows, or tool-calling architectures
• 2 years of experience in Highly regulated industry (healthcare, financial services) with HIPAA or equivalent compliance obligations
• 1 year of experience in Identity, access management, secrets handling, and runtime policy enforcement for AI workloads
• Master's degree in Cybersecurity, Computer Science, or a related field
• Certified Information Security Professional (CISSP)
• AWS Certified Security Specialty, Microsoft AZ-500, or Google Professional Cloud Security Engineer
• AI security credentials or coursework (SANS AI Security, NIST AI RMF practitioner training)