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# Agile Delivery Lead - AI & Automation

- **Company:** Reuters America LLC
- **Location:** Frisco, TX, United States
- **Experience:** Expert
- **Salary:** $118,400 - $219,800
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Microsoft Azure, Scrum Methodology, Generative AI, Agentic-AI
- **Published:** November 5, 2026
- **Apply:** https://diversityjobs.com/career/18831421/Agile-Delivery-Lead-Ai-Automation-Texas-Frisco

## About the Role

* Demonstrated experience leading the daily Agile delivery of high-output engineering, automation, or technology teams.
 * Deep practical understanding of small-batch delivery, cardinal prioritization, MVP development, iterative delivery, feedback loops, and limiting work in progress.
 * Ability to turn ambiguous ideas and business needs into clear, actionable backlog items, with experience in requirements clarification, story decomposition, backlog refinement, and meaningful acceptance criteria.
 * Comfort working with senior engineers, architects, and automation specialists, and the ability to constructively challenge complexity, unclear priorities, and excessive work in progress without relying on formal authority.
 * Skill in facilitating Agile practices that improve delivery, and the ability to explain clearly how to measure software-delivery effectiveness while staying open to learning and adapting.
 * Use of data to improve flow, support decisions, and communicate delivered value, with comfort in an environment where requirements evolve and learning is part of delivery.
 * Bachelor's degree or equivalent practical experience., * Certified ScrumMaster (CSM), Professional Scrum Master (PSM), PMI Agile Certified Practitioner (PMI-ACP), or equivalent demonstrated Agile delivery experience.
 * Experience delivering AI Agents, generative AI, intelligent automation, or workflow automation. This includes lightweight business analysis practices such as requirements elicitation, process mapping, user-story development, and acceptance-criteria definition.
 * Experience with Lean or Kanban practices, including WIP limits, cycle time, throughput, and aging-work analysis. ITIL Foundation certification or practical technology service-management experience is also beneficial.
 * Experience using Azure DevOps (ADO) or a similar backlog and delivery-management platform.
 * Experience delivering technology within enterprise security, governance, and responsible AI expectations.

## Description

As an Agile Delivery Lead, you will lead the daily delivery of small, high-impact automation initiatives, including AI Agents and other forms of automation. This is not a traditional project management role. You will work with experienced automation practitioners and engineers. Some are dedicated team members, and others rotate in from service delivery teams. Together you will create clarity, maintain focus, remove impediments, and deliver working solutions in small increments., * Lead day-to-day Agile delivery of AI and automation experiments, from initial idea through minimum viable product (MVP), validation, and production, with an emphasis on rapid feedback and maximizing learning.

 * Partner with LSM leaders, automation experts, and engineers to maintain a cardinally ordered backlog that makes clear what is first, second, and third in priority.
 * Make sure upcoming work is delivery-ready by facilitating requirements discovery, clarifying intended outcomes, and helping write well-defined user stories, acceptance criteria, and definitions of done.
 * Facilitate backlog refinement, daily coordination, iteration planning, reviews, and retrospectives. Adapt Agile practices to the team's needs instead of running ceremonies mechanically.
 * Break large or ambiguous opportunities into the smallest valuable increments, limit work in progress, and help the team finish the highest-priority work before starting more.
 * Quickly identify and clear barriers, resolve ambiguity, and bring the right experts together to keep priority work moving.
 * Use delivery data to identify bottlenecks, improve cycle time and throughput, support decisions, and communicate the value and learning the team produces.