VP- AI Platform and DevOps Engineer

About the role

Moody’s is seeking a VP- AI Platform and DevOps Engineer to lead the enterprise DevOps and AI platform strategy supporting internal artificial intelligence solutions. The ideal candidate will have executive-level experience leading DevOps, cloud infrastructure, or platform engineering teams in a large enterprise environment, with deep experience in managed Kubernetes platforms, Terraform, and CI/CD pipelines.

Responsibilities

• Define and execute the enterprise DevOps and AI platform strategy supporting internal artificial intelligence solutions
• Establish standards, governance, and operating models for cloud infrastructure
• Serve as a senior technical advisor on cloud, DevOps, and AI platform capabilities
• Own the foundational AI platform supporting enterprise tools and assume operational ownership of Moody’s Copilot infrastructure
• Lead DevOps for development and testing environments and drive Infrastructure as Code adoption using Terraform
• Oversee managed Kubernetes environments ensuring resilience and enhance developer experience through automation and tooling
• Host and maintain an MCP discovery tool enabling AI agent reuse and partner with AI and product teams to operationalize evaluation and monitoring
• Lead organizational transition of Copilot into Shared Services Technology Solutions Group

Requirements

• Bachelor's degree in Computer Science, Engineering, or related technical field
• Executive-level experience leading DevOps, cloud infrastructure, or platform engineering teams in a large enterprise environment
• Deep experience with managed Kubernetes platforms including Azure Kubernetes Service and Amazon Web Services
• Hands-on experience with Terraform and Infrastructure as Code
• Proficiency designing and governing CI/CD pipelines using enterprise tools such as GitHub Actions
• Strong background supporting artificial intelligence or data-driven platforms in production environments
• Demonstrated leadership driving complex platform transitions across organizational boundaries
• Proven ability to build scalable, secure, and repeatable DevOps practices
• Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization

Qualifications

• Experience with managed Kubernetes platforms including Azure Kubernetes Service and Amazon Web Services
• Hands-on experience with Terraform and Infrastructure as Code
• Proficiency designing and governing CI/CD pipelines using enterprise tools such as GitHub Actions
• Strong background supporting artificial intelligence or data-driven platforms in production environments
• Demonstrated leadership driving complex platform transitions across organizational boundaries
• Proven ability to build scalable, secure, and repeatable DevOps practices
• Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization

Skills

• Managed Kubernetes platforms (Azure Kubernetes Service, AWS)
• Terraform and Infrastructure as Code
• CI/CD pipelines (GitHub Actions)
• Artificial Intelligence
• Cloud Infrastructure
• DevOps Practices

Benefits

• Competitive benefits package including medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement

Pay

The anticipated hiring base salary range for this position is $170,000-$220,000, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation.

Schedule

Full-time position.