Cloud & Data Engineering Manager — AI Platform Leader

EY; Nashville (TN); Remote; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY is seeking a Data and Cloud Engineering Manager to turn data and AI capabilities into scalable production solutions. You will own workstreams, client interactions, budgets, and engagement economics while guiding technical talent and delivering reliable cloud platforms.

The role emphasizes hands-on cloud engineering with Kubernetes, GenAI/LLM integration, and Agile delivery, across Azure, AWS, and GCP platforms. National remote work supported in the US.

Qualifications

• Bachelor’s degree required (4-year degree).
• Typically, no less than 4–6 years of relevant experience.
• Proven record operating High Availability services on Azure (4+ years).
• Experience designing, deploying and managing container orchestration platforms using Kubernetes.
• Experience implementing SRE standards for resiliency and scalability of microservice architectures in Kubernetes.

Responsibilities

• Lead one or more technical workstreams and assure delivery quality.
• Translate business and client requirements into architecture, pipelines, models or production platforms.
• Maintain daily client engagement and identify adjacent service opportunities.
• Own budgets and engagement economics across projects.
• Work across data engineering, software engineering, AI/ML, and cloud governance to deliver scalable platforms.

Skills

Strong analytical skills

Self-starter

Education

Bachelor’s degree

Tools

Azure Functions

Azure Container Apps

Azure SQL Database

Azure Blob Storage

Azure Kubernetes Service (AKS)

Azure Monitor (Log Analytics & Application Insights)

Azure Managed Prometheus

Kubernetes

Terraform

GitHub Actions

Azure DevOps

CI/CD

Job description

EY is seeking a Data and Cloud Engineering Manager to turn data and AI capabilities into scalable production solutions. You will own workstreams, client interactions, budgets, and engagement economics while guiding technical talent and delivering reliable cloud platforms.

The role emphasizes hands-on cloud engineering with Kubernetes, GenAI/LLM integration, and Agile delivery, across Azure, AWS, and GCP platforms. National remote work supported in the US.