Lead Security Engineer - Artificial Intelligence

Testing Site - JPMC; Plano (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase in Plano, TX seeks a Lead Security Engineer - AI to join a high-performing Cybersecurity & Technology Controls team. You will shape secure software solutions and help prevent misuse while aligning with enterprise risk and regulatory standards.

You will design secure AI architectures, perform threat modeling and red-teaming exercises, and collaborate with product, data science, legal, and risk teams to strengthen AI resilience and incident response capabilities.

Qualifications

• Formal training or certification in Public Cloud environment concepts and advanced hands-on experience with cloud-native AI services (e.g., Bedrock).
• Threat modeling, discovery, vulnerability, and penetration testing (e.g., MITRE ATLAS, OWASP Top 10 for LLMs) and IAM/OIDC/SAML concepts.
• Infrastructure as Code (IaC) with Terraform and CloudFormation.
• Proficiency in Python scripting.
• Strong understanding of AI/ML concepts and AI red teaming foundations.
• Ability to design secure enterprise-level solutions and build internal tools and dashboards for red teaming.

Responsibilities

• Develop and enhance security strategies, red teaming programs, and scalable solutions.
• Design secure AI/software architectures and review designs for adversarial resilience.
• Reduce AI/LLM security vulnerabilities through standards, testing protocols, and controls.
• Collaborate with product, data science, cyber, legal, and risk teams on AI use cases and risk mitigation.
• Conduct discovery, threat modeling, and adversarial testing on generative AI and ML systems.
• Provide guidance on secure design, logging, monitoring, and compensating controls for AI apps.
• Define AI red teaming methodologies, playbooks, and metrics for safe rollouts.
• Coordinate with platform and cloud security teams to secure infrastructure alignment.
• Engage external researchers, vendors, and standards bodies on AI threats and best practices.
• Foster diversity, equity, inclusion, and respect within the team.
• Collaborate cross-functionally to influence AI risk tolerance and mitigation priorities.

Skills

Public Cloud

Threat Modeling

IaC

Python Scripting

AI/ML Concepts

Red Teaming

Adversarial Testing

Tools

Terraform

CloudFormation

PyRIT

Garak

Job description

Take on a crucial role whereyou'llbe a key part of a high-performing team delivering secure software solutions. Make a real impact as you help shape the future of software security at one of the world's largest and most influential companies.As a Lead Security Engineer - Artificial Intelligence at JPMorgan Chase within the Cybersecurity & Technology Controls for AI/ML, you are an integral part of team that works to deliver software solutions that satisfy pre-defined functional and user requirements with the added dimension of preventing misuse, circumvention, and maliciousbehavior. As a core technical contributor, youare responsible forcarrying out critical technology solutions with tamper-proof, audit defensible methods across multiple technical areas within various business functions.

Job Responsibilities

• Develop and enhance security strategies, red teaming programs, and solution designs, while troubleshooting technical issues and creating scalable solutions.
• Design secure, high-quality AI and software architectures, reviewing and challenging designs and code to ensure adversarial resilience.
• Reduce AI and LLM security vulnerabilities by adhering to industry standards and emerging AI safety research, evolving policies, testing protocols, and controls.
• Collaborate with stakeholders across product, data science, cyber, legal, and risk to understand AI use cases and recommend modifications during periods of heightened vulnerability or regulatory change.
• Conduct discovery, threat modeling, and adversarial testing on generative AI, RAG pipelines, and ML systems to identify vulnerabilities such as prompt injection, jailbreaking, and data poisoning.
• Provide guidance on secure design, logging, monitoring, and compensating controls for AI applications and platforms.
• Define and implement AI red teaming methodologies, playbooks, and success metrics, establishing mechanisms for continuous testing and safe rollout of new AI models and features.
• Work with platform and cloud security teams to ensure secure infrastructure configuration and alignment with enterprise security architecture.
• Engage with external researchers, vendors, and standards bodies to track emerging AI threats and bring best practices into the organization.
• Foster a team culture of diversity, equity, inclusion, and respect.
• Collaborate within a cross-functional team to develop relationships, influence senior stakeholders, and drive alignment on AI risk tolerance and mitigation priorities.

Required Qualifications, Capabilities, and Skills

• Formal training or certification in Public Cloud environment concepts and advanced hands-on experience with cloud-native AI services (e.g., Bedrock).
• Experience with threat modeling, discovery, vulnerability, and penetration testing (e.g., MITRE ATLAS, OWASP Top 10 for LLMs) and foundational cybersecurity concepts such as IAM, Authentication, OIDC, SAML.
• Practical experience with Infrastructure as Code (IaC) solutions like Terraform and CloudFormation.
• Proficiency in Python scripting.
• Strong understanding of AI/ML concepts and trends, with knowledge of AI red teaming foundational concepts to design and implement exercises for complex AI architectures.
• Ability to conceptualize, design, validate, and communicate creative technical solutions to enterprise-level security problems, including building internal tools, dashboards, and automation for red teaming activities.

Preferred Qualifications, Capabilities, and Skills

• Expertise in planning, designing, and implementing AI red teaming exercises and enterprise-level security solutions for generative AI, LLMs, and ML systems.
• Experience with specialized AI security/red teaming tools and frameworks (e.g., PyRIT, Garak, custom LLM evaluation harnesses) and contributions to AI security or open-source security projects.