AI Native Engineering Manager — Power & Utilities

EY; Minneapolis (MN); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Total Rewards package

Job summary

EY is seeking a Manager in AI Native Engineering to lead data science and big data initiatives for Power & Utilities clients in a globally connected, hybrid environment. You will collaborate with diverse teams, guide developers, and translate analytics into business insights while ensuring regulatory and governance standards are met.

You will work across regulated environments, leveraging SCADA, GIS, and other data sources to build scalable AI solutions, with heavy client interaction and

Qualifications

• Bachelor's degree required; 4-year degree.
• 6–10 years of AI/Data Science/Machine Learning experience.
• 2–4 years managing technical teams.
• Strong Python skills.
• Ability to lead and collaborate with diverse teams.
• Experience designing and maintaining production AI/ML solutions on major cloud platforms.
• Familiarity with DevOps, CI/CD, and ML workflows.

Responsibilities

• Lead workstream delivery and manage processes and projects.
• Identify innovative solutions through research and analysis.
• Supervise teams to deliver complex technical initiatives and ensure performance.
• Engage with clients and lead sessions from planning to closure.
• Identify opportunities for additional services and manage engagement economics.
• Design and deliver AI/ML use cases for Power & Utilities.

Skills

Python

Generative AI

DevOps

Data science

Team leadership

Education

Bachelor's degree

Master's degree

Tools

Git

Azure DevOps

Jira

OpenAI

LangChain

Job description

EY is seeking a Manager in AI Native Engineering to lead data science and big data initiatives for Power & Utilities clients in a globally connected, hybrid environment. You will collaborate with diverse teams, guide developers, and translate analytics into business insights while ensuring regulatory and governance standards are met.

You will work across regulated environments, leveraging SCADA, GIS, and other data sources to build scalable AI solutions, with heavy client interaction and