Lead AI Security Engineer

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Regular or Temporary: Regular Language Fluency:  English (Required) Work Shift: 1st shift (United States of America) Please review the following job description: • The Lead AI Security Engineer is a senior hands-on security engineer responsible for designing, implementing, and advancing controls that protect AI-enabled applications, agentic workloads, model integrations, and AI delivery pipelines across the full software and AI lifecycle. • This role focuses on securing agent behavior, prompt and context flows, tool invocation, data access, model interaction, pipeline integrity, runtime execution, observability, and deployment readiness in a regulated enterprise environment. • The engineer leads implementation of AI-specific security patterns including prompt-injection defenses, guardrails, output filtering, secure tool-use boundaries, identity and permission controls, evidence capture, logging, monitoring, and detection content for AI-enabled systems. • The work spans architecture review, threat modeling, adversarial test readiness, control validation, automation, detection engineering, deployment gating, production monitoring, and incident response support for AI and agentic solutions. • Daily work includes partnering with product, engineering, platform, data, risk, and security teams to translate AI security requirements into implementable controls that enable safe, traceable, resilient, and governed deployment of enterprise AI capabilities. ESSENTIAL DUTIES AND RESPONSIBILITIES Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time. Lead the design and implementation of security controls for AI-enabled applications, agents, model integrations, orchestration layers, and AI delivery pipelines. Perform AI and agentic threat modeling across prompts, context windows, retrieval flows, tools, APIs, permissions, memory, model access, data movement, and runtime execution paths. Implement and validate guardrails for prompt-injection resistance, unsafe output handling, tool-use abuse, sensitive data exposure, privilege escalation, model misuse, and policy-violating behavior. Build and maintain monitoring, alerting, and detection logic for AI systems, including anomalous prompts, abnormal agent actions, suspicious tool invocation, unsafe model responses, and control degradation. Embed security requirements into AI design reviews, acceptance criteria, validation plans, CI/CD or LLMOps workflows, model or prompt change controls, and release-readiness gates. Validate that AI solutions meet required security, governance, traceability, and evidence standards before release and continue to meet them after deployment. Support AI-related incident investigation, root-cause analysis, remediation planning, and operational response for suspicious behavior, control failures, data exposure, or unsafe system outcomes. Maintain control documentation, implementation guidance, runbooks, validation evidence, engineering patterns, and operating procedures for AI security engineering activities. Continuously improve AI security automation, validation workflows, detection content, guardrail logic, and deployment controls as models, agents, workflows, and attack techniques evolve. Required Qualifications: The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Bachelor’s degree or equivalent education, training, and work-related experience. Minimum of 10 years of experience in security engineering or related cybersecurity roles. Deep specialized knowledge in cybersecurity principles, theories, and concepts. Extensive experience in software development lifecycle security practices. Expertise in threat modeling, security testing, and penetration testing. Proven experience implementing and managing complex information security technologies. Additional Requirements: Minimum of 10 years of experience in security engineering, application security, product security, cloud security, cybersecurity operations, or related technical cybersecurity roles. Demonstrated experience leading complex security engineering efforts across modern software, API, cloud-native, automation, or platform environments. Strong understanding of AI, LLM, or agentic security risks, including prompt injection, insecure tool use, data exposure, model misuse, pipeline compromise, and unsafe output handling. Experience with threat modeling, security testing, control validation, detection engineering, logging, monitoring, or incident response for production systems. Ability to translate security requirements into implementable engineering controls, validation criteria, deployment gates, documentation, and operational runbooks. 3+ years of experience in a lead security engineering, application security, AI security, cybersecurity operations, or closely related technical discipline. Hands-on experience implementing controls for enterprise software, APIs, cloud-native services, workflow automation, model integrations, or agentic applications. Working knowledge of LLM and agentic security concepts such as prompt injection, indi