AI Security Engineer

Quantix, Inc. is seeking a Senior AI Security Engineer to help secure the organization's AI and machine learning ecosystem. This role involves partnering with various teams to identify and mitigate AI-related risks while establishing security standards for the responsible adoption of AI.

Responsibilities:

• Help secure the organization's AI and machine learning ecosystem
• Partner with Information Security, Engineering, IT, and business teams to identify, assess, and mitigate AI-related risks across the full AI lifecycle
• Help establish security standards, governance, and technical controls that enable the safe and responsible adoption of AI while protecting enterprise systems, data, and customers from emerging threats

Requirements:

• Bachelor's degree in Computer Science, Software Engineering, Information Security, or a related field or equivalent hands-on experience
• Minimum 8 years of experience in security engineering, information security, or related technical disciplines, with a demonstrated focus on securing AI/ML systems
• Proven experience defining and executing enterprise security strategies
• Experience and deep technical knowledge of how AI/ML technologies work
• Deep familiarity with AI security frameworks (e.g., NIST AI RMF, MITRE ATLAS, OWASP)
• Experience securing organizational tool stacks including cloud-based, hybrid or on-prem solutions
• Deep knowledge of AI related threats, risks and mitigation strategies
• Strong foundation in core security principles—threat modeling, secure design, and identity and access control—applied to AI/ML systems and the infrastructure that supports them
• Hands-on experience securing AI/ML systems, including practical AI red teaming against LLMs, agentic workflows, or RAG systems
• Strong programming and scripting proficiency (e.g., Python) for building security tooling, automation, and test harnesses across the AI/ML lifecycle
• Hands-on experience securing cloud and containerized environments (AWS, Azure, and/or GCP; Kubernetes and containers), including the infrastructure on which AI/ML workloads are trained, deployed, and served
• Experience embedding security into MLOps and AI/ML development pipelines (and the CI/CD workflows that feed them), including model and dataset integrity checks, guardrail validation, and automated security testing
• Proven ability to communicate complex security risk clearly to both technical and non-technical audiences, including engineers, leadership, and customers
• Demonstrated experience mentoring engineers and serving as a senior technical authority and subject-matter expert
• Hands-on offensive security and AI red-teaming experience targeting AI systems—including prompt injection, jailbreaks, data poisoning, model extraction, and agent/tool-abuse techniques—along with familiarity testing the web, API, and infrastructure layers these systems depend on
• Hands-on experience with AI/ML security tooling and AI security posture management (AI-SPM) platforms (e.g., Wiz AI-SPM, Protect AI, HiddeLayer, Lakera, or comparable model-scanning and guardrail solutions), complemented by familiarity with broader cloud and enterprise security platforms
• Hands-on experience securing AI/LLM-enabled and agentic applications, including deep familiarity with OWASP Top 10 for LLM Applications, OWASP Top 10 for Agentic AI, MITRE ATLAS, NIST AI RMF, and Model Context Protocol (MCP) security implications
• Practical experience with agent frameworks and orchestration (e.g., LaChain/LaGraph, CrewAI, AutoGen, or custom agent architectures) and with LLM evaluation, observability, and red-teaming tooling for testing model and agent behavior
• Experience operating within governance, risk, and compliance frameworks, with exposure to enterprise AI adoption, third-party/vendor AI risk assessment, and AI policy or standards development
• Experience in client-facing, consulting, or pre-sales roles, translating AI security concepts for customer and executive audiences through briefings, workshops, or advisory engagements
• Industry certifications such as CISSP, OSCP, or AWS/Azure/GCP security certifications; emerging AI-security-specific credentials (e.g., AI red-teaming or AI/LLM security certifications) are especially valued