AI Engineering Manager — Databricks & GenAI Solutions

EY; Denver (CO); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

401(k) plans

Paid time off

Job summary

EY is expanding its AI, Data & Engineering practice and seeks a Manager in Model Engineering to lead data and AI initiatives on the Databricks platform. You will guide diverse teams, interact with clients, and drive end-to-end delivery of scalable AI solutions, ML pipelines, and semantic data models.

You’ll collaborate with data scientists, engineers, and product stakeholders, ensuring responsible deployment, measurable business outcomes, and ongoing innovation across projects.

Qualifications

• 6-10 years in AI, Data Science, or Machine Learning
• 2-4 years directly managing technical teams
• 3-4 years building/ deploying production AI/ML on Databricks
• Databricks Certification (1+ professional, 1 associate)
• Strong Python, PySpark, and Scala skills
• Excellent communication and collaborative abilities

Responsibilities

• Lead AI workstreams from design to production on Databricks
• Build data pipelines and AI solutions (ML, GenAI, AgentAI)
• Drive product-centric AI delivery with measurable outcomes
• Collaborate with cross-functional teams and clients
• Ensure governance, quality, and responsible deployment
• Guide and mentor multidisciplinary teams across projects
• Advance Ontologies, knowledge graphs and semantic models

Skills

Python

PySpark

Databricks

AI/ML

Scala

Data engineering

MLOps

DevOps

AgentOps

Education

Bachelor's degree

Master's degree (preferred)

Tools

Git

Azure DevOps

Databricks tools

Databricks Certification

Job description

EY is expanding its AI, Data & Engineering practice and seeks a Manager in Model Engineering to lead data and AI initiatives on the Databricks platform. You will guide diverse teams, interact with clients, and drive end-to-end delivery of scalable AI solutions, ML pipelines, and semantic data models.

You’ll collaborate with data scientists, engineers, and product stakeholders, ensuring responsible deployment, measurable business outcomes, and ongoing innovation across projects.