Job Description
The Principal Cyber AI Engineer will drive the development and optimization of advanced tools, processes, and workflows to predict, detect, assess, and prevent AI-specific threats. This hands-on technical leadership role combines deep expertise in cybersecurity, AI security architecture, threat modeling, and security assessments to help ensure the safe adoption of AI technologies across the enterprise.
The ideal candidate will have direct experience assessing, securing, and remediating vulnerabilities in AI applications, AI platforms, agentic workflows, MCP-enabled architectures, and generative AI solutions deployed in production environments.
Key Responsibilities
• Design, develop, and optimize AI security threat models, controls, and architectures for AI applications, AI agents, and enterprise AI platforms.
• Perform security assessments and architecture reviews of AI solutions, including generative AI applications, agentic systems, MCP-based architectures, and AI-enabled workflows.
• Identify, analyze, and remediate AI-specific threats, including prompt injection, insecure tool usage, excessive agent permissions, model abuse, data leakage, and unauthorized access patterns.
• Implement and secure machine learning models, AI services, and agentic workflows to enhance threat detection, monitoring, and risk scoring capabilities.
• Partner with data scientists, AI engineers, security engineers, and platform teams to integrate security throughout the AI development lifecycle.
• Develop security controls, governance frameworks, guardrails, and monitoring capabilities for enterprise AI deployments.
• Analyze AI security incidents and assessment findings to improve AI security architecture, controls, and remediation strategies.
• Provide technical leadership and mentorship to engineers on AI security best practices, threat modeling, and secure AI design.
• Ensure alignment with industry standards such as NIST AI-RMF, ISO42001, OWASP Top 10 for LLM Applications, and emerging AI security practices.
• Stay current on advancements in AI, agentic systems, MCP architectures, AI attack techniques, and evolving cybersecurity threats.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience
• A Bachelor's or Master's degree in Computer Science, Engineering, Cybersecurity, or a closely related discipline is required.
• 10+ years of experience in cybersecurity engineering, application security, cloud security, or AI security within enterprise environments.
• Expertise in Python, R, Java, or similar programming languages.
• Deep understanding of machine learning, large language models (LLMs), agentic architectures, and AI application security.
• Demonstrated experience performing security assessments, threat modeling, and remediation activities for AI applications, AI platforms, or generative AI solutions.
• Hands-on experience identifying and mitigating AI-specific threats, including prompt injection, data leakage, model abuse, insecure tool access, agent privilege escalation, and unauthorized data exposure.
• Experience performing security reviews of AI systems, agent-based workflows, MCP-enabled architectures, APIs, and enterprise AI integrations.
• 3+ years of experience with Azure or AWS cloud-native services, architectures, and tools.
• Expertise in enterprise architectures, including cloud-native, AI, and distributed application security patterns.
• Advanced knowledge of security and governance frameworks, including NIST AI-RMF, ISO42001, and OWASP Top 10 for LLM Applications.
Strong communication skills with the ability to explain complex technical concepts and remediation strategies to both technical and non-technical stakeholders
Nice to Have Skills & Experience
• Experience securing Agentic AI systems, multi-agent architectures, and autonomous workflows.
• Experience securing or assessing Model Context Protocol (MCP) architectures, tool integrations, and agent communication frameworks.
• Experience conducting AI security testing, red teaming, penetration testing, or architecture reviews of AI applications.
• Demonstrated ability to lead cross-functional technical teams.
• Experience implementing AI security controls, guardrails, monitoring, and governance solutions in production environments.
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.