AI Security Engineer
About The Position
Trimble is seeking a senior individual contributor to serve as the enterprise’s dedicated AI security expert, connecting Agentic AI, Cyber Security, and AI Governance. The role focuses on securing AI agents, models, tool integrations, agentic workflows, and AI deployments against adversarial threats. The engineer will design adversarial scenarios, assess risks, establish automated safeguards, and create secure-by-default reference architectures for enterprise AI systems. The position partners with AI engineering teams and cross-functional security and governance groups to embed security controls throughout AI and MLOps lifecycles. It also contributes to enterprise AI security standards, supply-chain reviews, model risk assessments, and team education. The role is US-remote and requires 10% travel.
Requirements
- At least 5 years of security engineering or application security experience, with demonstrated technical depth in operational AI attack classes.
- Hands-on proficiency with Python, MLOps tooling, AI frameworks such as PyTorch or TensorFlow, and agent protocols such as MCP.
- Practical experience executing AI red-teaming using open-source tools such as PyRIT, Garak, or Promptfoo.
- Solid background in cloud security architecture across AWS, Azure, or GCP and containerized environment security.
- Strong working knowledge of the OWASP Top 10 for LLMs, OWASP agentic threat guidance, and NIST AI RMF standards.
Nice To Haves
- Experience with commercial AI security platforms, shadow AI discovery tools, or applied MITRE ATLAS tactics.
- Awareness of international AI governance frameworks, including ISO/IEC 42001 and the EU AI Act.
- Contributions to open-source AI security tools, published security research, CVEs, or industry conference speaking engagements.
- Relevant certifications such as OSCP, OSCE, AWS Security Specialty, or GIAC cloud security tracks.
Responsibilities
- Assess and secure AI agents, tool integrations, and agentic workflows, including permission scoping, action-chain risk, and non-human identity frameworks.
- Design and execute adversarial attack scenarios, including prompt injection, jailbreaking, insecure output handling, and data leakage across retrieval pipelines.
- Partner with AI engineers to establish automated security guardrails, vector store access controls, and output filtering policies across model lifecycles.
- Audit AI Ops pipelines, vet third-party AI supply-chain components, and lead model risk assessments before production deployment.
- Develop enterprise AI security standards.
- Train AppSec, SecOps, and GRC teams on AI-specific attack classes and threat mitigations.
Benefits
- Medical, dental, vision, life, and disability benefits.
- Time-off plans and retirement plans.
- Tax savings plans for health, dependent care, and commuter expenses, offered by most businesses.
- Paid parental leave.
- Employee Stock Purchase Plan.
- Bonus eligibility.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
