Manager, Automation & Enablement

Job Title

When you're the best, we're the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.

In this role, you will lead the day-to-day engineering delivery of Vizient's AI Intelligent Automation initiatives by managing one or more AI Automation Delivery PODs. You will be responsible for ensuring automation and AI solutions progress efficiently through the AI Delivery Lifecycle (AI-DLC), from engineering planning and sprint execution through testing, deployment, and production readiness.

You will partner closely with the Director, AI Intelligent Automation, who owns portfolio management, business priorities, governance, and organizational operations, and with the Lead AI Automation Engineer, who owns solution architecture, technology selection, and engineering standards. You will oversee Agile delivery execution, Azure Dev Ops planning, sprint management, engineering coordination, delivery reporting, release readiness, and continuous improvement to ensure predictable, high-quality delivery of enterprise automation solutions.

Success in this role is measured by the health and performance of AI Automation Delivery PODs, including delivery predictability, sprint execution, engineering throughput, release quality, operational excellence, and the consistent delivery of business value through enterprise AI and Intelligent Automation initiatives.

• Lead one or more AI Automation Delivery PODs responsible for delivering enterprise AI and Intelligent Automation initiatives through Vizient's AI Delivery Lifecycle (AI-DLC).
• Own the day-to-day execution of automation initiatives from engineering planning through deployment, ensuring predictable delivery, high quality, and operational readiness.
• Facilitate Agile delivery ceremonies including sprint planning, daily standups, backlog refinement, sprint reviews, retrospectives, and release planning.
• Manage Azure Dev Ops delivery activities including epics, features, user stories, tasks, bugs, sprint planning, work item quality, and delivery dashboards.
• Coordinate engineering work across Lead AI Automation Engineers, Senior AI Automation Engineers, AI Automation Engineers, QA resources, business analysts, contractors, and other delivery team members.
• Monitor sprint execution, engineering capacity, delivery progress, dependencies, risks, blockers, and resource utilization to ensure successful delivery commitments.
• Partner with the Director, AI Intelligent Automation to align engineering execution with approved portfolio priorities, staffing plans, business commitments, and organizational objectives.
• Partner with the Lead AI Automation Engineer to coordinate technical execution, solution readiness, engineering estimates, architecture reviews, production support planning, and engineering quality.
• Ensure automation initiatives progress through all phases of the AI Delivery Lifecycle (AI-DLC), including engineering, testing, user acceptance, production readiness, deployment, hypercare, and operational transition.
• Coordinate release planning, deployment activities, production readiness reviews, rollback planning, and post-production validation to ensure successful implementations.
• Prepare and communicate weekly delivery status reports, sprint metrics, engineering dashboards, delivery forecasts, risks, and mitigation plans for leadership.
• Track and report engineering delivery KPIs including sprint velocity, delivery predictability, cycle time, lead time, backlog health, release success, and delivery throughput.
• Balance engineering workloads across Delivery PODs by coordinating assignments, managing priorities, and proactively addressing resource constraints.
• Identify delivery risks early and work with engineering and business stakeholders to develop mitigation and recovery plans.
• Drive continuous improvement of Agile practices, Azure Dev Ops processes, AI-DLC execution, engineering workflows, delivery metrics, and operational efficiency.
• Coach and develop engineers in Agile delivery practices, engineering discipline, collaboration, accountability, and continuous improvement.
• Foster a collaborative, high-performing engineering culture focused on quality, transparency, predictable delivery, and customer satisfaction.
• Ensure engineering documentation, Azure Dev Ops artifacts, and delivery records are complete, accurate, and maintained throughout the AI Delivery Lifecycle.
• Support production operations by coordinating defect resolution, release stabilization, and continuous improvement activities following deployment.
• Perform other leadership responsibilities necessary to ensure the successful execution of enterprise AI and…