AI Engineering Operations Lead

Job Title: AI Engineering Operations LeadCWRs in NY or NJ are preferred; Remote is availableProfile Summary 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, and leveraging AI agents to automate administrative activities. The ideal candidate brings a combination of engineering operations experience, Agile delivery knowledge, process optimization skills, and practical application of AI-driven automation. They serve as the operational backbone of the Software Development Engineering organization, allowing engineers to focus on architecture, development, testing, code reviews, and delivering business value.Role Overview We are seeking an AI Engineering Operations Lead to support software development teams by owning the engineering operational activities required for efficient and predictable delivery. This role resides within the Software Development Engineering organization and serves as the operational partner to engineers, technical leads, Product Managers, Business Analysts, Architects, Scrum Masters, and Agile PMO. The primary responsibility of this role is to ensure that engineering work is accurately represented within Azure DevOps, development-ready artifacts are available for each iteration, engineering metrics and delivery data are captured and maintained, and administrative activities are automated wherever possible. 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. A key focus of the role is applying AI agents and automation to modernize engineering operations, reduce manual effort, improve engineering productivity, and allow software engineers to spend more time designing, building, testing, and delivering software.Key ResponsibilitiesOwn engineering operational execution within the Software Development Engineeringorganization.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 itemsare complete, synchronized, and aligned with SDLC and governance requirements.Partner with Product Managers, Business Analysts, Architects, and technical leads to ensurerequirements, specifications, acceptance criteria, dependencies, and supporting artifacts aredevelopment-ready before each iteration.Support engineering teams by managing operational activities that would otherwise consumedeveloper capacity.Ensure engineering metrics, delivery data, traceability information, and backlog health indicatorsare accurately captured, maintained, and validated within engineering systems of record.Provide complete and reliable delivery data that enables Agile PMO and leadership teams toperform stakeholder reporting, governance reviews, and portfolio oversight activities.Coordinate with Scrum Masters and Agile PMO to maintain alignment between engineeringexecution, planning activities, and governance requirements.Manage engineering work item hygiene, documentation quality, dependency tracking, releasereadiness, and audit traceability.Develop AI-powered agents and automation solutions to reduce manual administration, improvedata quality, and streamline engineering workflows.Leverage AI tools to automate documentation updates, backlog maintenance, traceabilitymanagement, engineering reporting inputs, and governance artifacts.Continuously identify opportunities to eliminate non-value-added engineering activities throughworkflow 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, governancecontrols, and automation frameworks.Act as the operational extension of the software engineering organization, enabling engineers tofocus on coding, architecture, testing, code reviews, and innovation.Required Experience10+ years of experience in software delivery, engineering operations, application developmentlifecycle 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, andrelease management.Experience working closely with Product Managers, Business Analysts, Architects, Developers, QAteams, and business stakeholders.Experience managing engineering operational processes, backlog governance, traceability, anddelivery data quality.Strong understanding of requirements management, acceptance criteria, dependencymanagement, and development readiness practices.Experience designing and implementing workflow automation solutions that improve engineeringproductivity and reduce manual effort.Strong analytical, organizational, communication, and stakeholder management skills.Experience operating within enterprise-scale technology organizations with establishedgovernance and compliance requirements.Familiarity with AI-assisted workflows, AI agents, engineering productivity tools, and GenAIplatforms.Demonstrated ability to leverage AI and automation to improve operational efficiency,documentation quality, reporting accuracy, and engineering effectiveness.Preferred Technical StackAzure DevOps for backlog management, work item administration, traceability, and engineeringoperations.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.MissionEnable software engineers to focus on building great software by owning engineering operationalexecution, ensuring development-ready artifacts and high-quality engineering data, and leveraging AIdriven automation to eliminate administrative overhead while supporting Agile delivery and governance processes.Success ProfileThe ideal candidate is passionate about improving engineering effectiveness and removing friction fromthe software development lifecycle. They understand both software engineering and delivery operationsand excel at transforming manual processes into streamlined, AI-enabled workflows.They act as a force multiplier for development teams by ensuring engineering systems, backlogs, metrics,and operational artifacts remain accurate, complete, and continuously optimized. Success is measuredby reduced administrative burden on software engineers, improved quality of engineering data andartifacts, increased automation, greater development readiness, and improved engineeringproductivity—not by ownership of Scrum ceremonies, Agile team facilitation, or stakeholder reporting responsibilities.Years of Experience: 9.00 Years of ExperienceApplicant Notices & DisclaimersFor information on benefits, equal opportunity employment, and location-specific applicant notices, click here