Job Description – Senior DevSecOps / MLOps Engineer (AI/ML Platforms) – Contractor
8+ years of experience
We are seeking a Senior DevSecOps / MLOps Engineer to drive security, compliance, and governance best practices across our AI/ML platforms on Azure and Databricks. This role will focus on embedding security into CI/CD pipelines, Kubernetes environments, and ML workflows to ensure secure, scalable, and compliant model development and deployment.
Key Responsibilities:
Implement DevSecOps practices across CI/CD pipelines (Azure DevOps) for AI/ML workloads
Secure Kubernetes (AKS) environments, including RBAC, network policies, and secrets management
Integrate security scanning, vulnerability management, and compliance checks into pipelines
Partner with Data Science, Platform, and Security teams to enforce secure MLOps practices
Drive governance standards for data, models, and platform access (e.g., least privilege, auditability)
Required Skills:
Strong experience with Azure DevOps, CI/CD, and DevSecOps practices
Hands-on expertise with Kubernetes (AKS) security and Azure cloud security controls
Experience securing AI/ML platforms (Azure ML, Databricks)
Knowledge of identity and access management, networking, and vulnerability management
Nice to Have: Terraform, policy-as-code, Microsoft Defender, secrets management (Key Vault), compliance frameworks
Job Description – Senior DevSecOps / MLOps Engineer (AI/ML Platforms) – Contractor
8+ years of experience
We are seeking a Senior DevSecOps / MLOps Engineer to drive security, compliance, and governance best practices across our AI/ML platforms on Azure and Databricks. This role will focus on embedding security into CI/CD pipelines, Kubernetes environments, and ML workflows to ensure secure, scalable, and compliant model development and deployment.
Key Responsibilities:
Implement DevSecOps practices across CI/CD pipelines (Azure DevOps) for AI/ML workloads
Secure Kubernetes (AKS) environments, including RBAC, network policies, and secrets management
Integrate security scanning, vulnerability management, and compliance checks into pipelines
Partner with Data Science, Platform, and Security teams to enforce secure MLOps practices
Drive governance standards for data, models, and platform access (e.g., least privilege, auditability)
Required Skills:
Strong experience with Azure DevOps, CI/CD, and DevSecOps practices
Hands-on expertise with Kubernetes (AKS) security and Azure cloud security controls
Experience securing AI/ML platforms (Azure ML, Databricks)
Knowledge of identity and access management, networking, and vulnerability management
Nice to Have: Terraform, policy-as-code, Microsoft Defender, secrets management (Key Vault), compliance frameworks
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