AI Platform Delivery Lead: Technical & Agile

EY; Greenville (SC); On-site; USD 144,000 - 329,000; Full time

Benefits offered by this job

Flexible vacation policy

Medical and dental coverage

Job summary

EY is seeking a seasoned Technical Delivery Manager to drive day-to-day execution for EY’s Agentic AI platform. You will manage delivery cadence across multiple development programs, run Scrum ceremonies, and ensure engineers meet commitments with evidence-backed focus on what’s in flight, blocked, or slipping.

Ideal candidates understand Kubernetes, GPU infrastructure, CI/CD, model serving, and agent orchestration, with credibility from hands-on engineering work.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field; equivalent depth.
• 7+ years in technical delivery, engineering project or program management with delivery accountability.
• Hands-on experience as software/platform engineer or equivalent technical depth.
• Ability to evaluate estimates, work decomposition, and technical risk with evidence.
• Experience running Scrum or Kanban for teams of experienced engineers.

Responsibilities

• Own the delivery cadence across multiple development programs and ceremonies.
• Track in-flight items to completion and surface slippage as it happens.
• Hold engineers to explicit definitions of done and dated commitments.
• Challenge estimates, sizing, and complexity with technical judgement.
• Break down architecture into properly sized, independently deliverable stories.

Skills

Technical depth

Agile delivery

Executive communication

Cloud-native / Kubernetes

CI/CD tooling

Jira / delivery tooling

GIT workflows

Education

Bachelor’s or Master’s in CS/Engineering

Tools

Kubernetes

CI/CD

Infrastructure as Code

Git-based workflows

Job description

EY is seeking a seasoned Technical Delivery Manager to drive day-to-day execution for EY’s Agentic AI platform. You will manage delivery cadence across multiple development programs, run Scrum ceremonies, and ensure engineers meet commitments with evidence-backed focus on what’s in flight, blocked, or slipping.

Ideal candidates understand Kubernetes, GPU infrastructure, CI/CD, model serving, and agent orchestration, with credibility from hands-on engineering work.