DevOps Engineer

Location: San Francisco, CA / Los Angeles, CA / New York, NY

Work Model: Hybrid – Onsite 10–12 days per month

Employment Type: Full-Time, Permanent

Salary Range: $160,000–$175,000 annually

About the Role: We are seeking an experienced AI DevOps Engineer to design, build, and manage automated CI/CD pipelines and infrastructure supporting AI, ML, Generative AI, and agentic AI applications across Microsoft Azure and on-premises environments.

Key Responsibilities: Design, develop, and maintain Azure DevOps YAML pipelines and reusable CI/CD components. Automate application build, testing, security validation, packaging, deployment, and release management. Manage containerization, artifact management, environment promotion, deployment verification, and rollback procedures. Support AI/ML application deployments across Azure and on-premises virtual machines or virtual desktop infrastructure. Collaborate with AI Software Engineers, ML Engineers, and infrastructure teams to define deployment and hosting requirements. Implement DevSecOps practices, access controls, configuration management, and change-control procedures. Protect sensitive, confidential, financial, and proprietary information.

Required Qualifications: Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field. Minimum 5 years of experience in DevOps, cloud engineering, platform engineering, or infrastructure engineering. At least 3 years of hands-on experience building and maintaining Azure DevOps CI/CD pipelines. Strong proficiency in Azure DevOps YAML, build and release automation, service connections, artifacts, deployment environments, approvals, variables, and access controls. Solid understanding of CI/CD, DevSecOps, automated testing, release management, and rollback strategies. Experience deploying and supporting containerized AI/ML, Generative AI, or data-intensive applications across Azure and on-premises environments.

Ideal Candidate: A hands-on DevOps professional with strong Azure DevOps pipeline expertise and experience operationalizing AI/ML applications in secure, enterprise environments.