Lead Security Engineer Red Team Plano, TX

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Description:
Take on a crucial role where youll be 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 worlds largest and most influential companies. As a Lead Security Engineer 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 malicious behavior. As a core technical contributor you are responsible for carrying out critical technology solutions with tamper-proof audit defensible methods across multiple technical areas within various business functions.

Job Responsibilities:

• Design develop and deploy enterprise-scale software applications and services solving business problems through strong software engineering practices with a focus on secure-by-design adversarial resilient AI-enabled systems.
• Participate in all SDLC phasesrequirements analysis solution design documentation implementation testing performance tuning automation production/non-production support and release managementincorporating enterprise architecture standards into application designs.
• Translate functional and technical requirements into high-quality application modules and microservices and develop secure high-quality production code for both AI and non-AI components aligned to predefined architectural specifications. Design secure AI and software architectures and conduct design and code reviews that challenge assumptions and validate security quality maintainability and adversarial resilience.
• Develop and enhance security strategies and red teaming programsdefining AI red teaming methodologies playbooks and success metricswhile troubleshooting technical issues and creating scalable solutions. Conduct discovery threat modeling and adversarial testing on generative AI RAG pipelines and ML systems to identify vulnerabilities such as prompt injection jailbreaking data poisoning and data leakage.
• Reduce AI/LLM vulnerabilities by adhering to industry standards and emerging AI safety research evolving policies testing protocols and controls and providing guidance on secure design logging monitoring and compensating controls. Write unit/integration test cases and establish robust CI/CD quality gates and handle production and non-production support by troubleshooting issues and improving operational readiness through monitoring logging and reliability enhancements.
• Lead evaluation sessions with external vendors researchers standards bodies and internal platform/cloud security teams to probe designs ensure secure infrastructure configuration and bring emerging AI threat best practices into the organization.
• Collaborate directly with stakeholders across product data science cyber legal and risk to analyze requirements and recommend modifications during heightened vulnerability or regulatory change; manage backlog documentation and release management across environments; and foster a cross-functional team culture of diversity equity inclusion and respect.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate threat modeling vulnerability analysis synthesis and security documentation validating outputs and ensuring sensitive data is handled appropriately.
• Applies reuse-first AI-assisted practices within SDLC/toolchain routines to strengthen security testing and control validation ensuring traceability/auditability and alignment to resiliency and security expectations.

• 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.

• 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