Senior AI Engineer: Databricks & Generative AI

EY; Milwaukee (WI); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY is seeking a Senior AI Engineer to lead the delivery of scalable AI and machine learning solutions on the Databricks platform. You will work closely with clients and EY teams to design, build, and deploy production-grade AI pipelines and agentic systems.

You will collaborate across data science, data engineering, and cloud engineering disciplines in a hybrid model (on-site and remote). A strong background in Python, PySpark, Scala, and Databricks is essential.

Qualifications

• Bachelor’s degree required in a relevant field.
• 3–6 years of full-time AI/ML experience.
• Databricks Certification required or equivalent.
• Strong programming in Python, PySpark, or Scala.
• Experience designing and deploying production AI/ML on Databricks.
• Proficient with DevOps tools (Git, Azure DevOps).
• Experience with MLOps, LLMOps, and Model Serving.

Responsibilities

• Research and implement scalable ML, generative AI, and agentic systems on Databricks.
• Build and maintain data engineering pipelines and AI solutions for clients.
• Evaluate, monitor, and optimize learning processes and models on Databricks.
• Collaborate with cross-functional teams to deliver production-grade AI solutions.
• Support client engagements with strong technical leadership and delivery.

Skills

Python

PySpark

Scala

Databricks

AI/ML

MLOps

AgentOps

Git

Azure DevOps

Education

Bachelor's degree

Master's degree

Databricks Certification

Tools

Databricks

Git

Azure DevOps

Job description

EY is seeking a Senior AI Engineer to lead the delivery of scalable AI and machine learning solutions on the Databricks platform. You will work closely with clients and EY teams to design, build, and deploy production-grade AI pipelines and agentic systems.

You will collaborate across data science, data engineering, and cloud engineering disciplines in a hybrid model (on-site and remote). A strong background in Python, PySpark, Scala, and Databricks is essential.