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About the Role

This job secures AI/ML, Generative AI, and agentic systems across the enterprise by designing, testing, and operating controls that protect these systems at scale in a regulated healthcare environment. The role combines hands-on adversarial testing, deep understanding of LLM and agent architectures, and production security expertise to prevent, detect, and contain AI-driven risk involving PHI, while advising engineering and security leadership on emerging AI threats and regulatory exposure.

Responsibilities

Design, implement, and operate security controls for AI/ML, GenAI, and agentic systems across model-level, data-level, and platform-level protections on Azure, GCP, AWS, and SaaS.
Engineer and enforce guardrails to mitigate prompt injection, unsafe outputs, unauthorized tool execution, data leakage, and insecure agentic workflow behavior, with a focus on PHI/PII exposure.
Design and execute AI red-team exercises targeting LLMs and AI agents, including prompt injection, 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, translating 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, implementing detection content for policy-violating AI behavior.
Embed security controls into CI/CD pipelines and agentic delivery workflows, partnering with AI platform, data engineering, and application teams to integrate security requirements from design through deployment.
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.
Perform 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).
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) using 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 a 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.

Skills

Deep working knowledge of AI/LLM security risks: prompt injection, unsafe outputs, tool-use abuse, data leakage, identity misuse, and agentic workflow escalation.
Hands-on proficiency with AI security frameworks: NIST AI RMF, MITRE ATLAS, OWASP LLM Top 10.
Cloud security fluency across Azure, GCP, and AWS, including native security tooling (Defender for Cloud, Wiz, GCP SCC).
Adversarial testing experience with AI red-team tooling (PyRIT, Promptfoo, AgentDojo, or custom harnesses).
Detection engineering — building monitoring logic, alerting pipelines, and telemetry for AI system behavior.
Proficiency in Python (or equivalent) for security automation, test harness development, and pipeline integration.
Secure API design, access controls, secrets management, and environment-based deployment controls for AI workloads.
HIPAA data handling requirements and PHI/PII protection considerations in AI pipelines and agentic workflows.
Strong written and verbal communication — capable of producing technical findings, remediation guidance, and executive security narratives.
Ability to operate effectively as a senior individual contributor in a large, matrixed healthcare organization.

Location

Office-Based or Remote Position

Work Type

Office-Based
Remote

Experience Level

5 years of experience in Cybersecurity engineering, application security, or platform security
3 years of experience in AI/ML or Generative AI security
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
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

Education Level

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.
Master’s degree in Cybersecurity, Computer Science, or a related field

Salary/Compensations

$94,200.00
$151,000.00

Benefits

Compliance Requirement: This job adheres to the ethical and legal standards and behavioral expectations as set forth in the code of business conduct and company policies.
As a component of job responsibilities, employees may have access to covered information, cardholder data, or other confidential customer information that must be protected at all times.
In connection with this, all employees must comply with both the Health Insurance Portability and Accountability Act of 1996 (HIPAA) as described in the Notice of Privacy Practices and Privacy Policies and Procedures as well as all data security guidelines established within the Company’s Handbook of Privacy Policies and Practices and Information Security Policy.
Furthermore, it is every employee’s responsibility to comply with the company’s Code of Business Conduct.
This includes but is not limited to adherence to applicable federal and state laws, rules, and regulations as well as company policies and training requirements.

About the Company

enGen

Equal Opportunity

Highmark Health and its affiliates prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities and prohibit discrimination against all individuals based on any category protected by applicable federal, state, or local law.
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For accommodation requests, please contact HR Services Online at HRServices@highmarkhealth.org
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