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# AI Cyber Security Engineer

- **Company:** StaffRight Associates
- **Location:** Dunkirk, NY, United States
- **Experience:** Expert
- **Salary:** $135,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, User Authentication, Microsoft Azure, Code Review, Continuous Delivery, Continuous Integration, Monitoring of Systems, Identity and Access Management, Information Systems Security Architecture Professional, Python (Programming Language), Key Management, Machine Learning, Network Segmentation, Red Team (Cyber Security), Search Technologies, Secure Coding, Software Engineering, Data Streaming, Data Logging, Google Cloud, Kubernetes, Hardware Acceleration, Machine Learning Operations, Docker
- **Published:** August 5, 2026
- **Apply:** https://www.dice.com/job-detail/2345abab-cc87-4605-b081-a15f5f4fa35f

## About the Role

* Eight or more years driving hands-on security architectures across application, cloud, or infrastructure domains within live production environments.
 * Hands-on familiarity with Artificial Intelligence Systems, Machine Learning Pipelines, Large Language Model Applications, Vector Search, and Machine Learning Operations Platforms.
 * Demonstrated history establishing Authentication, Authorization, Secrets Management, Network Segmentation, and secure Continuous Integration and Continuous Delivery frameworks.
 * Deep knowledge of Amazon Web Services, Microsoft Azure, Google Cloud Platform, Docker, and Kubernetes.
 * Technical mastery of risks like Data Poisoning, Model Theft, Adversarial Attacks, Model Inversion, Prompt Injection, and Jailbreaking.
 * High proficiency using Python, Go, or Java.
 * Solid expertise in Secure Software Development, Code Review, and Security Design Review.
 * Outstanding communication skills to articulate risks and technical trade-offs to non-technical business partners and engineering peers alike.

## Description

* Architect and execute holistic protection strategies across all machine learning ecosystems, safeguarding training pipelines, inference nodes, feature repositories, and data flows.
 * Analyze architectural vulnerabilities and run threat assessments targeting risks like model inversion, prompt manipulation, data corruption, and unauthorized exploitation.
 * Engineer custom automated monitoring mechanisms and security tooling capable of identifying and neutralizing artificial intelligence threats, adversarial manipulations, and abnormal usage sequences.
 * Partner directly with data science professionals to embed security protocols throughout the development lifecycle, conducting red team exercises and enforcing secure code standards.
 * Harden external integrations, large language model interfaces, vector repositories, and agentic workflows through rigorous identity management, access controls, and logging protocols.
 * Coordinate with infrastructure teams to lock down containerized clusters, hardware acceleration resources, registry tools, and continuous delivery systems against compliance standards.
 * Establish advanced telemetry and monitoring systems to track suspicious platform usage, detect operational drift, and capture threat metrics.
 * Lead digital investigations alongside incident management teams to analyze logs, platform activity, and potential model compromise during security events.
 * Champion technical guidance and cross-functional mentorship regarding secure systemic design, threat landscapes, and defensive architectures.
 * Formulate governance frameworks, corporate standards, and operational boundaries for ethical technology usage, covering prompt handling and dataset classification.


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