Lead Engineer - AI Security; Remote Eligible

Lead Engineer AI Security Team

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here . Target's security team is a place where innovation happens daily. Join our team to improve Target's security and move the business forward.

As a Lead Engineer on the AI Security team, you'll collaborate with technical and leadership teams across Target Tech to assess, validate, and continuously improve the security of AI systems and platforms. You will identify security risks and gaps in existing AI implementations, evaluate the effectiveness of security controls and mitigations, perform architectural and technical reviews, and provide actionable recommendations to strengthen the overall security posture of AI solutions.

This role is highly technical, requiring deep expertise in AI security, threat modeling, security controls, testing methodologies, and industry standards. You will serve as a trusted advisor and hands-on expert, helping teams identify emerging risks, validate security assumptions, and drive continuous improvements as AI capabilities are deployed, scaled, and evolved across the enterprise.

Beyond the deep technical expertise, you have great interpersonal skills: our Lead Engineers are called upon to collaborate across the enterprise and have exceptional communication skills that enable open and cooperative partnerships.

Expect to:

• Collaborate with AI platform, product, and engineering teams to evaluate the security posture of AI systems throughout their lifecycle
• Define and evaluate security assessment methodologies, testing frameworks, and assurance standards for AI technologies
• Develop and execute security validation strategies for AI systems, including threat modeling, attack simulation, and adversarial testing
• Conduct deep technical reviews of AI products, platforms, and architectures to identify opportunities for security improvement
• Partner with engineering teams to validate secure deployment patterns for AI workloads across cloud and hybrid environments
• Assess AI architectures, models, agents, and supporting infrastructure to identify security risks, vulnerabilities, and design weaknesses
• Evaluate the effectiveness of existing security controls, guardrails, and mitigations protecting AI applications and platforms
• Perform hands-on security analysis and testing of complex AI-enabled systems, identifying gaps in architecture, implementation, and operational controls
• Recommend risk mitigation strategies and prioritized remediation plans to improve the security and resilience of AI systems
• Provide expert guidance on AI security best practices, including model security, prompt injection defenses, agent security, supply chain security, and data protection
• Prioritize high-impact security improvements that measurably reduce risk while enabling innovation and business objectives
• Identify emerging AI-specific threats, attack techniques, and vulnerabilities, and communicate their potential business impact
• Collaborate with security, architecture, and engineering teams to continuously improve AI security controls and governance practices
• Efficiently assess and communicate security risks to stakeholders, balancing technical realities, business priorities, and organizational objectives
• Serve as a trusted advisor on AI security, helping teams make informed decisions as AI capabilities evolve across the enterprise

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

About You:

• 4-year degree or equivalent experience
• Software developer comfortable in several programming languages across different platforms
• 7+ years of hands-on experience in technology, with deep knowledge of multiple cybersecurity domains including Information Protection, Cloud Security (GCP strongly preferred), Networking Security, IAM, Automation, and SIEM
• LLM Security expertise (RAG, MCP, input validation, sandboxing etc.)
• In-depth understanding of OWASP Top 10 for Large Language Model Applications
• Solid understanding of AI and ML
• Understanding of prompt injection and its various styles (direct, indirect, RAG poisoning, etc.)
• Knowledge of MCP authentication patterns including dynamic client registration
• Knowledge of RAG authorization patterns
• Experience mitigating the security risks of local coding agents
• Solid understanding of containerization technologies and tools
• Seeks out cross-team collaboration opportunities
• Demonstrates curiosity and ability to learn
• Stays current on relevant technologies with self-directed learning
• Excellent written and verbal interpersonal skills with strong presentation abilities
• Proven history of effectively utilizing a variety of security tools and technologies across diverse environments. The ideal candidate will not be limited to specific vendors or solutions but will possess the technical depth to comprehend and implement an end-to-end solution that aligns…