AI/ML Engineering Lead — Power & Utilities (Remote)

EY; Indianapolis (IN); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical & dental coverage

401(k) plan

Paid time off

Job summary

EY is seeking a Manager in AI Native Engineering to lead teams delivering scalable AI/ML solutions for Power & Utilities clients. You will work with diverse global teams, translate AI outcomes into business insights, and drive governance, security, and regulatory alignment across engagements.

The role emphasizes client interaction, project delivery, and leadership of technical teams, with a strong emphasis on data science, software engineering, and cloud-based production systems.

Qualifications

• 6-10 years of relevant experience in AI, Data Science, and/or Machine Learning.
• 2-4 years of experience directly managing technical teams.
• Strong skills in Python and experience designing, building production AI/ML solutions on major cloud platforms.
• Experience with Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, RAG) and ML packages like scikit-learn and PyTorch.

Responsibilities

• Lead workstreams and ensure effective delivery of complex technical initiatives.
• Engage actively with clients, guiding sessions from planning through execution to closure.
• Translate AI and analytics outputs into business-relevant insights for executives and operational leaders.
• Support production deployment of AI solutions while meeting regulatory and governance requirements.

Skills

Python

Team leadership

Client engagement

Communication

Regulatory understanding

Education

Bachelor's degree

Tools

OpenAI

Langchain

PyTorch

GIT

Azure DevOps

Job description

EY is seeking a Manager in AI Native Engineering to lead teams delivering scalable AI/ML solutions for Power & Utilities clients. You will work with diverse global teams, translate AI outcomes into business insights, and drive governance, security, and regulatory alignment across engagements.

The role emphasizes client interaction, project delivery, and leadership of technical teams, with a strong emphasis on data science, software engineering, and cloud-based production systems.