Managed Services Technical Delivery Lead - AI Accelerated Delivery

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Technical Delivery Lead (AI Accelerated Delivery)

Our current scale necessitates a dedicated role in Control Tower. This role is essential to drive the delivery and solution teams for MS Control Tower, it is and to enable integrations of various solutions and provide robust support for the client's data processing capabilities.

For this, we require a seasoned technical leader who has demonstrated an impressive technical acumen and aligns well with our high standards. The expertise and skillset of such an individual should significantly contribute to driving our product roadmap forward and achieving our ambitious goals. This role is to be an internal position within CTMS for EY, ensuring that we have the right technical delivery leadership to propel the Control Tower roadmap further.

We plan to have Sudeshna (currently loaned from the Tech Consulting team) aligned with this role – she has been with the ADA product team as an Architect, for over two years and demonstrated high levels of commitment on the overall architecture and delivery. We all believe that her unique qualifications and the positive impact on our diversity goals make her an ideal candidate for this role.

 

Core Responsibilities            

• Support discussions with business analysts, product managers, architects, and other key stakeholders to understand functional and non functional requirements, and to scope delivery effort (time, cost, and risk).
• Coordinate the allocation of software development resources to product initiatives, balancing delivery priorities, skills, and capacity.
• Coordinate development planning activities including sprint definition, milestones, timelines, and dependency management.
• Coordinate with DevOps, Data Services, and platform teams as part of the overall delivery governance and release lifecycle.

 

AI Enabled and Accelerated Delivery Responsibilities

• Direct and enable rapid application development through the effective use of AI assisted engineering tools such as GitHub Copilot and similar developer productivity platforms.
• Define and promote standards and guardrails for the responsible use of AI assisted coding, ensuring alignment with enterprise architecture, security, quality, and compliance requirements.
• Drive the adoption of automation techniques across the software delivery lifecycle, including:
  • Automated code generation and refactoring
  • Test automation (unit, integration, and regression)
  • CI/CD pipeline automation
  • Infrastructure as Code and environment provisioning
• Work with engineering leads to redefine delivery practices (e.g., backlog refinement, sprint execution, code reviews) to fully exploit AI enabled development while maintaining code quality and maintainability.
• Ensure AI generated code is subject to appropriate review, validation, and observability, integrating automated quality, security, and performance checks into the delivery pipeline.
• Partner with DevOps and platform teams to embed AI and automation capabilities into development toolchains, improving deployment frequency, lead time, and stability.

 

Leadership, Governance, and Continuous Improvement

• Act as a delivery orchestrator, aligning people, process, tools, and technology to maximize speed to value without compromising control.
• Provide guidance and coaching to delivery teams on modern engineering practices, including AI assisted development, automation first design, and shift left quality.
• Track and report on delivery performance using flow and productivity metrics (e.g., lead time, cycle time, deployment frequency), highlighting the impact of AI and automation on outcomes.
• Continuously identify opportunities to improve delivery efficiency through new tools, patterns, and practices, and lead controlled experimentation and adoption.
• Serve as a key interface between business stakeholders and engineering teams, translating delivery acceleration into measurable business value.

 

 

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