DevOps Engineer - Machine Learning Data Engineering

Workday is seeking a security-focused DevOps Engineer to support its AI-driven contract intelligence platform. The role designs and manages AWS and GCP cloud infrastructure, integrates security throughout the SDLC, operates AI agent frameworks in production, and improves automation, monitoring, scalability, and developer productivity.

Responsibilities:

• Design, build, deploy, and manage security tools and services across cloud infrastructure environments
• Remediate security vulnerabilities within cloud and application infrastructure
• Integrate security practices at every stage of the SDLC and deployment pipelines
• Build and manage CI/CD pipelines, continuously improving reliability, speed, and lead time for changes
• Deploy and operate AI agent frameworks such as LangGraph, AWS Bedrock Agents, LangChain, or CrewAI in production environments
• Analyze system performance and capacity, planning proactively for future growth
• Secure infrastructure at both the cloud layer (IAM) and application layer (PKI)
• Build and expand monitoring and alerting systems for infrastructure and business operations using internal and third-party SaaS tools
• Establish and maintain comprehensive infrastructure-as-code coverage across the entire platform
• Develop tools and automation to enhance developer productivity and reduce operational overhead
• Champion automation of manual processes across engineering and security operations

Requirements:

• Strong knowledge of the Kubernetes ecosystem, including EKS cluster management
• Proficiency with cloud platforms such as AWS, Azure, or GCP and containerization technologies including Docker and Kubernetes
• Hands-on experience with CI/CD tools, particularly GitHub Actions
• Scripting and programming proficiency in Python, Bash, Go, or TypeScript
• Experience with infrastructure-as-code tools such as Terraform, CloudFormation, or Ansible
• Practical experience building and operating AI agents or LLM-powered systems including tool-calling, multi-step workflows, memory and context management, and evaluation
• Understanding of platform, application, and cloud security fundamentals
• Ability to architect, analyze, and support complex distributed systems
• Experience debugging and optimizing systems and application code
• Familiarity with service mesh concepts and frameworks such as Istio or Linkerd within Kubernetes clusters
• Security-centric approach to infrastructure-as-code, Docker build pipelines, and microservice deployments
• 5+ years of experience in DevOps, security operations, or software development
• 5+ years of experience building and managing EKS clusters with strong Kubernetes ecosystem knowledge
• Proven track record of building tooling, automation, and services in one or more programming languages
• Demonstrated experience deploying and managing AI agents or LLM-powered systems in production environments
• Relevant certifications in cloud platforms such as AWS Certified DevOps Engineer, Google Professional DevOps Engineer, or equivalent are a plus
• Background or coursework in computer science, software engineering, information security, or a related technical discipline preferred