Manager, Intelligent Automation & Enablement

Vizient•Chicago, IL

2d•$117,600 - $206,000•Onsite

About The Position

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 DevOps 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.

Requirements

Relevant bachelor's degree in Computer Science, Information Systems, Software Engineering, Engineering, Business, or a related field preferred.
5+ years of experience in software engineering, enterprise technology delivery, automation, engineering operations, project management, or related technical disciplines.
3+ years of experience leading Agile software engineering teams, engineering delivery organizations, or enterprise technology initiatives.
Experience managing software development projects through the Software Development Lifecycle (SDLC) using Agile delivery methodologies.
Experience leading Scrum teams and facilitating Agile ceremonies including sprint planning, backlog refinement, daily standups, sprint reviews, and retrospectives.
Experience managing engineering work using Azure DevOps, Jira, or comparable Agile project management platforms.
Experience coordinating cross-functional engineering teams consisting of software engineers, quality engineers, business analysts, architects, contractors, and business stakeholders.
Experience managing engineering capacity, delivery schedules, dependencies, risks, and resource allocation across multiple concurrent initiatives.
Experience preparing executive-ready delivery status reports, project dashboards, KPIs, and risk assessments.
Working knowledge of enterprise Intelligent Automation platforms including UiPath, Microsoft Power Platform, and AI-enabled automation technologies.
Understanding of enterprise software engineering practices including SDLC, DevOps, CI/CD, release management, production support, and change management.
Experience coordinating production deployments, release readiness activities, operational support, and post-production stabilization.
Strong organizational, planning, communication, facilitation, and problem-solving skills with the ability to manage multiple priorities in a fast-paced environment.
Proven ability to build collaborative relationships across engineering, business, and operational teams while fostering accountability, transparency, and continuous improvement.
Ability and willingness to work onsite in Vizient's Irving, Texas office.

Responsibilities

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 DevOps 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 DevOps 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 DevOps 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 Intelligent Automation initiatives.