Senior Technical Delivery Lead for AI Platform

EY; San Mateo (CA); Remote; USD 160,000 - 230,000; Full time

Job summary

EY seeks a seasoned Technical Delivery Manager to lead day-to-day execution of engineering teams building EY’s Agentic AI platform. You will own delivery cadence across multiple programs, run Scrum ceremonies, track progress, and ensure commitments are met with evidence-based decisions.

The role requires hands-on technical depth in cloud-native systems (Kubernetes, CI/CD, model serving) and the credibility to challenge estimates, decompose work, and protect the team from distractions while

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• 7+ years in technical delivery, engineering project or program management roles.
• Hands-on experience as a software or platform engineer or equivalent depth.

Responsibilities

• Own the delivery cadence across the engineering teams with daily stand-ups, planning, backlog refinement and reviews.
• Drive progress against commitments and surface slippage as it happens.
• Hold engineers to defined done criteria and dated commitments; escalate when delivery is at risk.
• Interrogate estimates, test sizing, and challenge padding with evidence.
• Break down architecture and platform work into deliverable stories with clear acceptance criteria.
• Own sprint and release planning across the phased platform build to deliver usable capability.
• Manage cross‑discipline dependencies and risk with transparency to leadership.

Skills

Technical depth

Agile leadership

Strong communicator

Delivery ownership

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

Jira

Git

Kubernetes

CI/CD

Job description

EY seeks a seasoned Technical Delivery Manager to lead day-to-day execution of engineering teams building EY’s Agentic AI platform. You will own delivery cadence across multiple programs, run Scrum ceremonies, track progress, and ensure commitments are met with evidence-based decisions.

The role requires hands-on technical depth in cloud-native systems (Kubernetes, CI/CD, model serving) and the credibility to challenge estimates, decompose work, and protect the team from distractions while