AI Security Engineer

Job Position

AI Security Engineer
Role Summary
The AI Security Engineer at NXP Semiconductors will be responsible for securing Machine Learning (ML), Generative AI (GenAI), and Agentic AI solutions deployed across enterprise and engineering environments. This role focuses on identifying, assessing, and mitigating security risks associated with Large Language Models (LLMs), retrieval systems, AI agents, model integrations, AI-assisted development tools, and enterprise AI platforms.
The AI Security Engineer will collaborate with AI solution teams, application teams, cloud/platform engineering, enterprise security, and architecture teams to ensure solutions are deployed securely and aligned with NXP security standards, risk management practices, and regulatory requirements.
The ideal candidate will have hands-on experience in application security, cloud-native security, and secure software engineering practices, with strong understanding of AI-related attack vectors such as prompt injection, insecure tool usage, model abuse, data leakage, retrieval poisoning, and insecure model integrations.
This role will support AI security assessments, runtime security controls, AI security testing, and implementation of scalable security guardrails to enable secure enterprise AI adoption and AI-enabled engineering workflows.
Your Opportunity
NXP is a global player in Semiconductor industry, and security is an essential and integral part of our business.
Job Responsibility
1.AI Security Assessments
Conduct security assessments for AI/ML/GenAI use cases and platforms
Evaluate AI systems for risks related to prompt injection, insecure outputs, data leakage, unsafe tool execution, model misuse, and retrieval poisoning
Review AI integrations involving APIs, plugins, MCP servers, external tools, vector databases, and enterprise data sources
Support threat modeling activities for AI-powered applications and agentic workflows
AI Runtime Security and Control Implementation
Support the implementation of AI runtime security controls, monitoring, and policy enforcement mechanisms
Assist in securing AI gateways, inference endpoints, and AI service integrations
Help define security guardrails for prompts, agent execution, and model interactions
Contribute to observability and monitoring capabilities for AI systems, including logging, auditing, and anomaly detection
3.Secure AI Development and Engineering Practices
Collaborate with engineering teams to integrate secure development practices into AI/ML/GenAI workflows
Support secure deployment and configuration of AI applications across cloud and enterprise environments
Assist with validating secure use of AI coding assistants and AI-enabled development tools
4.Collaboration and Stakeholder Engagement
Collaborate with Enterprise Architects, Application Security teams, Cloud Security teams, Data Scientists, AI Engineers, and Business stakeholders
Support AI onboarding and security review processes for new AI initiatives and platforms
Provide security guidance and recommendations to development and product teams
Participate in discussions related to AI governance, risk management, and enterprise AI adoption
5.Risk Management and Compliance
Support implementation of controls aligned with industry frameworks such as NIST AI RMF, OWASP Top 10 for LLM Applications, and secure AI engineering best practices
Identify and support remediation of security risks associated with AI systems, models, datasets, and third-party AI services
Assist in evaluating AI solutions for compliance with internal security requirements and applicable regulations
Support security investigations related to AI systems and integrations
Job Qualification
Desired Education
Bachelor’s degree in computer science, Cybersecurity, Engineering, Information Technology, or a related field
Advanced degrees such as Masters are preferred
Professional Experience
5+ years of experience in Cybersecurity, Application Security, Cloud Security, or related engineering roles
2+ years of experience supporting or securing AI/ML/GenAI applications or platforms
Experience with secure software development lifecycle (SSDLC), application security, 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, Azure.
Technical Skills
Understanding of AI/ML/GenAI concepts including LLMs, RAG architectures, embeddings, vector databases, and AI agents
Knowledge of AI-related attack vectors and security risks including prompt injection, indirect prompt injection, insecure tool access, and model abuse
Familiarity with OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI RMF concepts
Knowledge of container security, API security, IAM, secrets management, and cloud security fundamentals
Understanding of secure coding and software security principles
Soft Skills
Strong analytical and problem-solving skills
Excellent communication and collaboration abilities
Ability to manage multiple initiatives in a fast-paced environment
Certifications (Preferred)
AI/ML-related and cybersecurity certifications are considered a plus
More information about NXP in the United States...
NXP is an Equal
Opportunity/Affirmative
Action Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, NXP will provide reasonable accommodations for otherwise qualified disabled individuals.
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