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Lenovo Digital Trust Lab is seeking a hands-on AI SecOps Expert to strengthen the security and resilience of our AI/ML pipelines and hybrid AI infrastructure. This role will focus on integrating DevSecOps practices into AI pipelinesensuring data, models, and orchestration layers are protected from design to deployment.

As part of the Hybrid AI Security team, you will own the security lifecycle of AI workloads, embedding guardrails, monitoring, and automation into development, training, and inference workflows. You will work closely with researchers, engineers, and product teams to transform cutting-edge AI security research into repeatable, production-grade security practices.

Job Responsibilities

• Design and implement secure-by-default CI/CD pipelines for AI/ML workflows (data ingestion, feature engineering, training, inference).
• Integrate security testing and validation into AI DevOps processes (e.g., model integrity checks, adversarial robustness tests, dataset validation).
• Automate compliance and governance controls across AI pipelines, ensuring traceability and audit readiness.
• Build and maintain monitoring and logging frameworks to detect anomalies, data poisoning, and model manipulation in real time.
• Collaborate with researchers and engineers to operationalize security tools across data, build, inference, and orchestration stages.
• Drive adoption of zero-trust principles in AI development workflows, including container, API, and cloud security hardening.
  
  

Minimum Requirements

• B.Sc. or M.Sc. in Computer Science, Cybersecurity, Data Engineering, or related technical field.
• 5+ years of hands-on experience in DevOps / SecOps / Cloud Security.
• Proven expertise with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, Argo, etc.) and container orchestration (Kubernetes, Docker).
• Solid understanding of AI/ML pipelines (data preparation, training, deployment, monitoring).
• Strong background in secure coding practices, threat modeling, and vulnerability management.
• Experience with logging, monitoring, and alerting systems (ELK/EFK, Prometheus, Grafana).
  
  

Preferred Requirements

• Experience with MLOps platforms (Kubeflow, MLflow, SageMaker, Databricks).
• Familiarity with adversarial ML, model supply-chain security, and AI-specific threats.
• Hands-on experience with infrastructure as code (Terraform, Helm, Ansible).
• Knowledge of cloud-native security (AWS, Azure, GCP security services).
• Contributions to open-source DevSecOps, AI security, or related projects.
  
  

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.