AI Security Engineer: Build Secure ML Pipelines

TechDigital Group; Bolingbrook (IL); On-site; USD 120,000 - 170,000; Full time

Job summary

TechDigital Group in the United States is seeking an AI Engineer focused on security for the expanding AI program. This hands-on role builds tooling, pipelines, and controls to secure AI initiatives and enable secure-by-design development across the enterprise.

You will collaborate with data science and platform teams to embed security requirements into the AI development lifecycle, implement risk detection, and integrate with SIEM/SOAR and monitoring tools while advancing guardrail automation

Qualifications

• 3+ years in security or ML engineering with hands-on AI/LLM systems.
• Proficiency in Python and ML/LLM frameworks and security tooling.
• Experience with cloud platforms (Azure/AWS/GCP) and IAM/secrets management.
• Knowledge of AI threat models and secure-by-design practices.

Responsibilities

• Design, build, and maintain tooling for AI asset discovery and model inventory.
• Implement security controls for AI pipelines, including data protection and deployment security.
• Integrate AI risk signals into SIEM/SOAR and monitoring platforms.
• Build automated testing and red-teaming harnesses for AI apps.
• Support secure integration of third-party and internal AI/LLM services.
• Collaborate to embed security requirements into the AI development lifecycle.

Skills

AI/ML security

Python

CI/CD security

Threat modeling

Security engineering

Tools

LangChain

Hugging Face

TensorFlow

PyTorch

Guardrail frameworks

Model scanning tools

SIEM/SOAR

Splunk

Cloud platforms (Azure/AWS/GCP)

Job description

Must have skill: AI/ML

Job Description: The AI Engineer will build and operationalize the tooling, pipelines, and controls that secure 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.

Preferred Qualifications
• Experience with SIEM/SOAR platforms (Splunk, Sentinel, etc.) and scripting integrations.
• Security certifications (Security+, GCIH, OSCP) or cloud certifications (AWS/Azure Security).
• Prior retail or PCI-regulated environment experience.