AI Engineering Operations Lead

Role Description

AI Engineering Operations Lead with strong expertise in software delivery operations, Azure DevOps engineering governance, SDLC processes, and AI-enabled workflow automation. This role focuses on enabling high-performing software engineering teams by:

• Owning engineering operational execution
• Ensuring development-ready artifacts
• Maintaining engineering systems of record
• Leveraging AI agents to automate administrative activities

The ideal candidate brings a combination of:

• Engineering operations experience
• Agile delivery knowledge
• Process optimization skills
• Practical application of AI-driven automation

This role does not replace Scrum Masters or Agile PMO responsibilities; rather, it enables those functions by ensuring the engineering organization maintains high-quality operational data, traceability, backlog hygiene, and governance artifacts that support delivery management and stakeholder reporting.

Key Responsibilities

• Own engineering operational execution within the Software Development Engineering organization
• Maintain Azure DevOps backlogs, work item structures, workflows, dependencies, traceability, and engineering documentation required to support delivery execution
• Ensure MVPs, Epics, Features, User Stories, Technical Tasks, Defects, and engineering work items are complete, synchronized, and aligned with SDLC and governance requirements
• Partner with Product Managers, Business Analysts, Architects, and technical leads to ensure requirements, specifications, acceptance criteria, dependencies, and supporting artifacts are development-ready before each iteration
• Support engineering teams by managing operational activities that would otherwise consume developer capacity
• Ensure engineering metrics, delivery data, traceability information, and backlog health indicators are accurately captured, maintained, and validated within engineering systems of record
• Provide complete and reliable delivery data that enables Agile PMO and leadership teams to perform stakeholder reporting, governance reviews, and portfolio oversight activities
• Coordinate with Scrum Masters and Agile PMO to maintain alignment between engineering execution planning activities and governance requirements
• Manage engineering work item hygiene, documentation quality, dependency tracking, release readiness, and audit traceability
• Develop AI-powered agents and automation solutions to reduce manual administration, improve data quality, and streamline engineering workflows
• Leverage AI tools to automate documentation updates, backlog maintenance, traceability management, engineering reporting inputs, and governance artifacts
• Continuously identify opportunities to eliminate non-value-added engineering activities through workflow simplification and automation
• Drive adoption of AI-enabled engineering operations practices while remaining aligned with Agile SDLC compliance and governance standards
• Establish repeatable operational processes that improve backlog quality, development readiness, traceability, engineering productivity, and delivery predictability
• Contribute to documentation of engineering standards, operating procedures, governance controls, and automation frameworks
• Act as the operational extension of the software engineering organization, enabling engineers to focus on coding, architecture, testing, code reviews, and innovation

Qualifications

• 10 years of experience in software delivery, engineering operations, application development lifecycle management, technical program management, or related engineering support functions
• Deep experience with Azure DevOps including Boards, Backlogs, Work