AI Security Engineering Lead

The position is described below. If you want to apply, click the Apply Now button at the top or bottom of this page. After you click Apply Now and complete your application, you'll be invited to create a profile, which will let you see your application status and any communications. If you already have a profile with us, you can log in to check status. Need Help? If you have a disability and need assistance with the application, you can request a reasonable accommodation. Send an email to Accessibility (accommodation requests only; other inquiries won't receive a response). Regular or Temporary: Regular Language Fluency:  English (Required) Work Shift: 1st shift (United States of America) Please review the following job description: The AI Security Engineering Lead is a senior technical leader responsible for securing the organization's adoption of artificial intelligence, generative AI, and agentic technologies across the enterprise. This role combines technical leadership, consulting, and hands-on security engineering to ensure AI-enabled solutions are secure, resilient, governed, and production-ready. Operating within the Forge AI Security organization, this individual serves as a trusted advisor and security partner to engineering, product, platform, architecture, governance, risk, and cybersecurity teams. The role leads security reviews, architecture assessments, threat modeling exercises, control validations, adversarial testing activities, and deployment readiness reviews for AI-enabled applications, intelligent agents, retrieval-augmented generation (RAG) solutions, and enterprise AI platforms. The AI Security Engineering Lead works directly with delivery teams throughout the development lifecycle, helping teams identify risks, implement security controls, validate configurations, and remediate findings while accelerating the secure adoption of AI technologies. This role regularly supports multiple concurrent initiatives, acting as the primary AI security consultant embedded within project teams during critical phases of solution design, build, testing, and deployment. The position needs a talent with deep expertise in cybersecurity engineering and modern AI technologies, including no-code, low-code, and pro-code development approaches. The role supports AI solutions operating across cloud platforms, with a primary focus on Microsoft Azure and growing adoption of AWS services, including Amazon Bedrock. This is a lead individual contributor position that influences technical direction and security outcomes across multiple teams while remaining deeply involved in hands-on implementation, engineering, validation, testing, and operational support activities. ESSENTIAL DUTIES AND RESPONSIBILITIES The following is a summary of the essential functions for this role. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time. AI Security Architecture and Design Lead security architecture reviews, threat modeling exercises, and design assessments for AI-enabled applications, agents, and enterprise AI platforms. Define secure design patterns and reference architectures for generative AI, agentic systems, RAG solutions, model integrations, and AI-enabled workflows. Establish and evolve AI security standards, security guardrails, and technical implementation patterns across the enterprise. Evaluate new AI technologies and architectures to identify risks, security requirements, and appropriate control strategies. AI Security Engineering and Implementation Design, implement, configure, and validate technical security controls for AI-enabled solutions across development, testing, and production environments. Build and enhance AI security capabilities, including access controls, logging, monitoring, output protections, security automation, and deployment controls. Develop technical guardrails that reduce the risk of prompt injection, indirect prompt manipulation, unauthorized tool use, sensitive data exposure, privilege escalation, and other AI-specific attack scenarios. Partner with engineering teams to implement secure patterns for tool calling, workflow orchestration, model access, agent permissions, data retrieval, and external system integrations. Support security integration within no-code, low-code, and pro-code AI development environments. Security Reviews and Validation Lead AI security assessments, control validations, architecture reviews, and deployment readiness evaluations. Validate that AI solutions meet enterprise security, governance, safety, and compliance requirements before release. Review implementations for adherence to approved security standards, guardrails, and operational controls. Conduct hands-on testing and validation activities to identify security weaknesses and implementation gaps. Support adversarial testing, misuse-case analysis, red-teaming activities, and remediation planning. Detection, Monitoring, and Response Design and maintain monitoring, alerting, and detection capabilities for AI and agentic systems. Develop telemetry requirements and detection logic designed to identify suspicious prompts, anomalous agent behavior, unauthorized tool usage, policy violations, and other security concerns. Partner with cybersecurity operations and incident response teams to investigate and remediate AI-related security events. Improve observability capabilities that support the monitoring and operational governance of AI systems. Consulting and Technical Leadership Serve as the primary AI security consultant for multiple concurrent delivery initiatives and platform efforts. Provide practical, actionable security guidance to engineering teams throughout the software development lifecycle. Translate complex AI security risks into implementable controls, technical requirements, engineering standards, and remediation p