AI Application Security Engineer
NXP Semiconductors is hiring an AI Application Security Engineer in Austin (on-site) to secure AI-powered applications, GenAI/RAG systems, and APIs. Day to day: security assessments, architecture reviews, pen testing, and embedding secure coding and SSDLC practices using OWASP LLM Top 10, NIST AI RMF, and cloud platforms like AWS/Azure.
- Compensation
- Not disclosed
- Location
- Austin (Oakhill, Office)
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Security
- Posted
Skills
Must have
- Bachelor's degree in Computer Science, Cybersecurity, Engineering, Information Technology, or related field
- 5+ years of experience in Cybersecurity, Application Security, Runtime Security, or related engineering roles
- 2+ years of experience supporting or securing AI/ML/GenAI applications or platforms
- Experience with SSDLC, security testing, and cloud-native security practices
- Experience with AI/ML platforms, APIs, orchestration frameworks, or AI-assisted development environments
- Familiarity with cloud platforms such as AWS or Azure
- Understanding of AI/ML/GenAI concepts including LLMs, RAG architectures, APIs, vector databases, and AI-assisted applications
- Knowledge of application security principles: secure coding, API security, authentication/authorization, tenant isolation
- Knowledge of AI-related attack vectors: prompt injection, insecure outputs, insecure plugins, retrieval poisoning
- Familiarity with OWASP Top 10 for LLM Applications, OWASP ASVS, MITRE ATLAS, and NIST AI RMF
- Knowledge of cloud-native application security, container security, IAM, secrets management, and software security principles
- Strong analytical and problem-solving skills
- Excellent communication and collaboration abilities
- Ability to manage multiple initiatives in a fast-paced environment
Nice to have
- Master's degree
- AI/ML-related and cybersecurity certifications
Full description
Job Title: AI Application Security Engineer
Job Position: AI Application Security Engineer
Role Summary
The AI Application Security Engineer at NXP Semiconductors will be responsible for securing AI-powered applications, APIs, Generative AI (GenAI) solutions, and retrieval-augmented generation (RAG) systems deployed across enterprise and engineering environments. This role focuses on securing the application layer of AI systems, including authentication and authorization flows, prompt handling, API integrations, data access patterns, session management, and secure interaction with enterprise systems.
The AI Application Security Engineer will work closely with application development teams, AI engineering teams, enterprise security, and architecture teams to ensure AI applications are designed, developed, and deployed securely in alignment with NXP security standards and secure software engineering practices.
The ideal candidate will have strong hands-on experience in Application Security, secure coding, API security, cloud-native applications, and modern AI application architectures, with understanding of AI-related risks such as prompt injection, insecure outputs, data leakage, insecure plugins, and retrieval poisoning.
This role will support secure AI application development, architecture reviews, AI application security testing, and implementation of scalable application-layer security controls to enable secure enterprise AI adoption.
Your Opportunity
NXP is a global player in Semiconductor industry, and security is an essential and integral part of our business.
Job Responsibility
- Conduct application security assessments and secure design reviews for AI-powered applications and GenAI solutions
- Review AI integrations involving APIs, plugins, RAG pipelines, vector databases, and enterprise applications
- Evaluate risks related to prompt injection, insecure outputs, data leakage, insecure APIs, and retrieval poisoning
- Support secure software development lifecycle (SSDLC) practices for AI applications and AI-enabled development workflows
- Collaborate with engineering teams to implement secure coding practices, application-layer controls, and secure authentication and authorization mechanisms
- Support AI application penetration testing, API security testing, and remediation activities
- Assist with validating secure use of AI coding assistants and AI-enabled development tools
- Support implementation of controls aligned with NIST AI RMF, OWASP Top 10 for LLM Applications, and secure application engineering practices
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