Lead Engineer – AI Security

Target

. Collaborate with AI platform, product, and engineering teams to evaluate AI system security throughout the lifecycle .

Posted 9/18/2026full-timeBrooklyn Park • Minnesota • United StatesSenior💰 $132,000 - $238,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI security, including threat modeling, attack simulation, and security validation strategies. Proficient in evaluating security controls and frameworks while collaborating with cross-functional teams to enhance AI system security across cloud and hybrid environments.

Highest-signal resume keywords

AI Security ExpertiseCloud Security (GCP Preferred)Information ProtectionSecurity Frameworks (NIST, ISO/IEC 27001)Hands-On Security Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Threat ModelingAdversarial TestingInput ValidationContainerization TechnologiesNetwork SecurityCryptographySecure Software DevelopmentRAG Authorization PatternsMCP Authentication PatternsOWASP Top 10 for Large Language Model Applications

Soft Skills

Excellent Communication SkillsStrong Presentation AbilitiesAnalytical Problem-Solving SkillsInterpersonal Skills

Tools & Technologies

SIEMFirewallsIDS/IPSDLPGCP Native Security ProductsCommercial Security ProductsVertex AIAWSAzure

Industry Keywords

Security Assessment MethodologiesSecurity Validation StrategiesRisk Mitigation StrategiesEmerging AI-Specific ThreatsSecurity Management Workflows

Tech Stack

Tools & technologies

AWSAzureCloudFirewallsGoogle Cloud Platform

About the role

Key responsibilities & impact

Collaborate with AI platform, product, and engineering teams to evaluate AI system security throughout the lifecycle
Define and evaluate security assessment methodologies, testing frameworks, and assurance standards for AI technologies
Develop and execute security validation strategies, including threat modeling, attack simulation, and adversarial testing
Conduct technical reviews of AI products, platforms, and architectures
Validate secure deployment patterns for AI workloads across cloud and hybrid environments
Assess AI architectures, models, agents, and supporting infrastructure for security risks and vulnerabilities
Evaluate security controls, guardrails, and mitigations protecting AI applications and platforms
Perform hands-on security analysis and testing of complex AI-enabled systems
Recommend risk mitigation strategies and prioritized remediation plans
Provide guidance on model security, prompt injection defenses, agent security, supply chain security, and data protection
Prioritize security improvements that reduce risk while enabling innovation and business objectives
Identify emerging AI-specific threats, attack techniques, and vulnerabilities
Communicate security risks and potential business impact to stakeholders
Collaborate with security, architecture, and engineering teams to improve AI security controls and governance
Serve as a trusted advisor on AI security across the enterprise

Requirements

What you’ll need

4-year degree or equivalent experience
Software developer comfortable in several programming languages across different platforms
7+ years of hands-on experience in technology
Deep knowledge of Information Protection, Cloud Security (GCP strongly preferred), Network Security, IAM, Automation, and SIEM
LLM Security expertise, including RAG, MCP, input validation, and sandboxing
In-depth understanding of OWASP Top 10 for Large Language Model Applications
Solid understanding of AI and ML
Understanding of direct, indirect, and RAG poisoning prompt injection
Knowledge of MCP authentication patterns including dynamic client registration
Knowledge of RAG authorization patterns
Experience mitigating security risks of local coding agents
Solid understanding of containerization technologies and tools
Excellent written and verbal interpersonal skills with strong presentation abilities
Proven history utilizing varied security tools and technologies across diverse environments
Good understanding of security management workflows in large enterprise organizations and complex environments
Good understanding of the current threat landscape
In-depth knowledge of security frameworks, standards, and best practices, including NIST and ISO/IEC 27001
Strong understanding of network security, cryptography, and secure software development
Experience with firewalls, IDS/IPS, SIEM, and DLP
Excellent analytical, problem-solving, and communication skills
Preferred: GCP native security product experience
Preferred: Commercial security product experience
Preferred: LLM Security expertise
Preferred: Vertex AI experience
Preferred: AWS or Azure experience

Benefits

Comp & perks

Comprehensive health benefits and programs, which may include medical, vision, dental, and life insurance
401(k)
Employee discount
Short term disability
Long term disability
Paid sick leave
Paid national holidays
Paid vacation
Financial, education, and well-being benefits