at Teksystems in Bolingbrook, Illinois, United States Job Description Description Role Summary The AI Engineer will build and operationalize the tooling, pipelines, and controls that secure Ulta's growing portfolio of AI initiatives. This is a hands-on engineering role responsible for implementing AI/ML security controls, integrating AI risk detection into existing security tooling, and supporting secure-by-design AI development practices across the enterprise. Key Responsibilities Design, build, and maintain tooling for AI/ML asset discovery, model inventory, and shadow-AI detection across the enterprise. Implement security controls for AI pipelines, including data protection, access control, secrets management, and secure model deployment (MLOps/LLMOps security). Integrate AI risk signals (e.g., prompt injection attempts, data exfiltration via AI tools, anomalous model behavior) into existing SIEM / SOAR and monitoring platforms. Build automated testing and red-teaming harnesses for AI applications (adversarial testing, jailbreak/prompt-injection testing, data leakage testing). Support secure integration of third-party and internally built AI/ LLM services ( API gateways, guardrail middleware, output filtering). Collaborate with data science, platform engineering, and application teams to embed security requirements into the AI development lifecycle (secure-by-design, CI/CD gates). Document control implementations, runbooks, and technical standards for AI security engineering. Required Qualifications 3+ years in security engineering, cloud engineering, or ML engineering, with direct hands-on exposure to AI/ML or LLM -based systems. Proficiency in Python and experience with ML/ LLM frameworks (e.g., LangChain, Hugging Face, TensorFlow/PyTorch) or AI security tooling (e.g., guardrail frameworks, model scanning tools). Working knowledge of cloud platforms (Azure and/or

AWS / GCP

) and cloud-native security controls ( IAM , network segmentation, key/secrets management).

Familiarity with AI-specific threat models:

prompt injection, model inversion, data poisoning, insecure output handling, excessive agency ( OWASP Top 10 for LLM Applications). Experience with CI/CD pipelines, infrastructure-as-code, and integrating security tooling into automated pipelines. Skills Security, Information security, engineering management, AI Security, AI Top Skills Details Security,Information security,engineering management,AI Security,AI Additional Skills & Qualifications Preferred Qualifications Experience with

SIEM / SOAR

platforms (Splunk, Sentinel, To view full details and how to apply, please login or create a Job Seeker account