AI Engineering Operations Lead (Azure DevOps & GenAI)

Our Client, an IT Services and Consultant company, is looking for an AI Engineering Operations Lead (Azure DevOps & GenAI) for their New York, NY/ NJ/ Remote location.
 
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.

• 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 Item Management, Queries, Dashboards, and workflow administration.
• Strong understanding of Agile delivery, SDLC processes, software engineering practices, and release management.
• Experience working closely with Product Managers, Business Analysts, Architects, Developers, QA teams, and business stakeholders.
• Experience managing engineering operational processes, backlog governance, traceability, and delivery data quality.
• Strong understanding of requirements management, acceptance criteria, dependency management, and development readiness practices.
• Experience designing and implementing workflow automation solutions that improve engineering productivity and reduce manual effort.
• Strong analytical, organizational, communication, and stakeholder management skills.
• Experience operating within enterprise-scale technology organizations with established governance and compliance requirements.
• Familiarity with AI-assisted workflows, AI agents, engineering productivity tools, and GenAI platforms.
• Demonstrated ability to leverage AI and automation to improve operational efficiency, documentation quality, reporting accuracy, and engineering effectiveness.
• Preferred technical stack
• Azure DevOps for backlog management, work item administration, traceability, and engineering operations.
• Microsoft Copilot, GitHub Copilot, Claude, ChatGPT, or similar AI platforms.
• Power Automate, Copilot Studio, Logic Apps, and other workflow automation technologies.
• Power BI and dashboarding platforms for engineering operational analytics.
• Jira, Confluence, SharePoint, and enterprise collaboration platforms.
• SQL, Excel, and reporting tools for delivery insights and operational analysis.
• Microsoft Teams and related collaboration technologies.

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities