Cyber AI Security & Forensic Engineer – IT & OT

3Core Systems , Inc•Denver, CO

5d•Hybrid

About The Position

We are seeking experienced Cyber AI Security & Forensic Engineers to help identify, assess, and mitigate emerging cybersecurity risks associated with Artificial Intelligence, Large Language Models (LLMs), Generative AI, and autonomous/agentic AI systems. There are two openings for this position: IT Cyber AI Security & Forensic Engineer: Focused on enterprise applications, cloud environments, LLM/GenAI applications, APIs, AI agents, and application security. OT Cyber AI Security & Forensic Engineer: Focused on applying AI security and cybersecurity principles within Operational Technology (OT), Industrial Control Systems (ICS), SCADA, and industrial environments. The ideal candidates will have a strong cybersecurity foundation combined with hands-on experience assessing AI/LLM applications, identifying vulnerabilities and bypass techniques, recommending security controls, and applying security frameworks such as OWASP.

Requirements

Bachelor's degree in Cybersecurity, Computer Science, Information Technology, Engineering, or a related field, or equivalent experience.
Strong cybersecurity engineering, application security, penetration testing, or security assessment experience.
Hands-on experience with AI/ML security, LLM security, Generative AI security, or AI application testing.
Understanding of common LLM and AI vulnerabilities, attack techniques, and security controls.
Experience with OWASP Top 10 and preferably OWASP LLM Top 10 / OWASP Agentic AI security concepts.
Experience with threat modeling, vulnerability assessment, security testing, and risk analysis.
Understanding of authentication, authorization, API security, data protection, and least-privilege principles.
Experience analyzing security findings and providing practical remediation recommendations.
Strong analytical, troubleshooting, documentation, and communication skills.

Responsibilities

Perform security testing of AI applications, LLMs, Generative AI solutions, and AI-enabled platforms to identify vulnerabilities, weaknesses, misuse cases, and potential bypass techniques.
Conduct AI/LLM security assessments, including testing for prompt injection, jailbreaks, data leakage, insecure outputs, model manipulation, and unauthorized access.
Evaluate AI applications and integrations for security weaknesses across APIs, data sources, tools, plugins, and external services.
Assess agentic AI architectures and autonomous software agents to understand how agents interact with external tools, APIs, data, and enterprise systems.
Evaluate agent permissions, tool access, authentication, authorization, and least-privilege controls.
Identify risks associated with excessive agency, insecure tool use, indirect prompt injection, and unauthorized actions.
Recommend secure AI and data usage practices, including data protection, access controls, secure prompts, guardrails, and responsible AI practices.
Apply OWASP Top 10, OWASP API Security Top 10, OWASP LLM Top 10, and other applicable security standards to identify and communicate security risks.
Perform threat modeling and security assessments for AI-enabled applications and services.
Work with application, cloud, data, infrastructure, and cybersecurity teams to remediate identified vulnerabilities.
Support vulnerability management, incident investigations, digital forensics, and root-cause analysis where required.
Review logs, telemetry, application behavior, and security events to identify suspicious or malicious AI activity.
Develop security recommendations, assessment reports, remediation plans, and technical documentation.
Stay current with emerging AI attack techniques, LLM vulnerabilities, agentic AI risks, and AI security frameworks.
Assess security of enterprise LLM/GenAI applications, APIs, cloud services, RAG solutions, vector databases, and AI integrations.
Test AI applications for prompt injection, jailbreaks, sensitive information disclosure, insecure output handling, and data poisoning.
Review AI integrations with enterprise applications, SaaS platforms, APIs, and external tools.
Evaluate cloud security controls across AWS, Azure, or GCP environments.
Support application security, API security, secure SDLC, SAST/DAST, and DevSecOps initiatives.
Analyze AI application logs and telemetry for security anomalies and potential abuse.
Apply AI and cybersecurity security practices to Operational Technology environments, including ICS, SCADA, PLC, DCS, and industrial control systems.
Assess security risks associated with AI-enabled OT applications and autonomous systems.
Understand OT network architecture, segmentation, remote access, industrial protocols, and OT security controls.
Support OT incident response, threat hunting, forensic investigations, and security assessments.
Evaluate the potential impact of AI-driven attacks or compromised AI systems on industrial environments.
Work closely with OT engineering, controls, infrastructure, and cybersecurity teams to identify and mitigate risks.