AI Transformation Delivery Manager Job Description Reports to AI Transformation Lead Location DFW preferred; Remote considered for strong candidates Work type Contract-to-Hire (Hourly) Travel None currently About Us Transformativ helps organizations redesign core business processes for an AI-first operating environment. Our teams lead the business process redesign and build the AI, machine learning, workflow, and other automation needed to make the redesigned process work in practice. Position Summary The AI Transformation Delivery Manager connects our AI transformation leaders, client teams, and AI engineers. The role turns a target-state process design into an executable roadmap and then into clear requirements that engineers can build, test, and release. The position is approximately 50 percent program and project management and 50 percent business analysis. It requires someone who can impose practical structure on ambiguous work, operate with limited supervision, and keep decisions focused on business value and delivery. Focus Primary partners Purpose 50 percent Delivery management AI transformation leaders and client leaders Create and drive the roadmap, release plan, workstreams, milestones, decisions, and dependencies required to deliver the redesigned process. 50 percent Business analysis Client subject matter experts and AI engineers Define the requirements, rules, data, controls, exceptions, and acceptance criteria for AI and other automation. Our Approach to Delivery This is a hands-on delivery role rather than a traditional PMO position. We use agile methods pragmatically and apply only the structure needed to clarify priorities, manage risk, accelerate decisions, and deliver measurable results. Success is not defined by strict adherence to PMBOK or by producing project documentation that does not help the team deliver. A PMP certification is not required. The business analysis work also differs from a conventional current-state documentation role. This person must help define a process that may not yet exist and specify how people, AI agents, automation, data, and controls will work together in the redesigned process. Key ResponsibilitiesTransformation Planning and Delivery

• Work with AI transformation leaders to convert target-state process designs into prioritized roadmaps, releases, workstreams, milestones, and near-term delivery plans.
• Define intended business outcomes and practical measures of value with client and transformation leaders, then use those measures to guide scope and priorities.
• Lead day-to-day delivery across business and engineering workstreams, maintaining momentum without adding unnecessary process or administration.
• Plan and facilitate agile delivery activities, including backlog refinement, release planning, progress reviews, decision sessions, and retrospectives.
• Identify dependencies, assumptions, risks, and unresolved decisions early; bring forward clear options and recommendations when leadership input is needed.
• Track delivery against outcomes, scope, milestones, and acceptance criteria, and adjust the plan as the team learns. Business Analysis and Solution Definition
• Facilitate working sessions with client leaders, subject matter experts, transformation leaders, and engineers to define how the redesigned process should operate.
• Translate process designs into buildable functional requirements, user stories, acceptance criteria, business rules, data requirements, exception paths, and nonfunctional requirements.
• Specify the roles of AI agents, machine learning, workflow automation, system integrations, and human judgment within the process.
• Define human-in-the-loop approvals, confidence thresholds, escalation paths, audit requirements, and other controls appropriate to the business risk.
• Document inputs, outputs, interfaces, dependencies, and decision logic clearly enough for engineers and testers to act without repeated interpretation.
• Maintain requirements and backlog clarity as prototypes, technical constraints, user feedback, and delivery priorities evolve. Business and Engineering Alignment
• Give engineers the business context behind requirements so that technical decisions support the intended process outcome.
• Explain technical constraints, choices, and tradeoffs to business stakeholders in clear language and help the team reach timely decisions.
• Keep transformation leaders, client stakeholders, and engineering teams aligned on scope, priorities, decisions, and the definition of done.
• Support demonstrations, validation, testing readiness, release decisions, and the transition of new capabilities into the redesigned process. What Success Looks Like
• Ambiguous transformation objectives become a coherent, prioritized delivery roadmap with clear ownership and decision points.
• Requirements describe the future process and are detailed enough for engineering teams to estimate, build, and test with minimal rework.
• Business and technical teams share the same outcomes, scope, constraints, and acceptance criteria, and deliver useful increments as they learn.
• Risks, exceptions, and human oversight requirements are addressed early, and delivered capabilities produce measurable, sustainable process improvements. Required Qualifications
• At least six years of experience spanning technology delivery, program or project management, product delivery, business analysis, or closely related roles.
• Demonstrated ability to lead complex, technology-enabled initiatives from an ambiguous objective through requirements, build, testing, and release.
• Strong business analysis skills, including process design, facilitation, requirements definition, user stories, acceptance criteria, business rules, data requirements, and exception handling.
• Experience working in agile or iterative delivery environments and managing a backlog, priorities, dependencies, risks, and stakeholder decisions.
• Excellent written and verbal communication, including the ability to make complex business and technical issues understandable to executives, subject matter experts, and engineers.
• Sound judgment, intellectual curiosity, and strong client-facing skills, with the ability to work independently, build credibility without formal authority, and escalate when needed.

Technical Fluency The successful candidate does not need to be an AI engineer, but must be technically fluent enough to work productively with engineering teams and challenge unclear assumptions. This includes a practical understanding of:

• Generative AI, large language models, agentic AI, machine learning, workflow automation, and where each is appropriate.
• APIs, system integrations, data models, data quality, and the movement of data through an automated process.
• Security, privacy, auditability, model limitations, human oversight, and operational controls for AI-enabled solutions.
• Prototyping, testing, deployment, monitoring, and iterative improvement of software and AI capabilities. Preferred Experience
• Consulting or other client-service experience in which priorities, stakeholders, and requirements evolved during delivery.
• Business process redesign or enterprise transformation involving functions such as finance, human resources, procurement, legal, operations, marketing, or shared services.
• Experience defining requirements for AI-enabled products, intelligent automation, decision support, workflow platforms, or data-intensive applications.
• Experience designing a future-state process rather than limiting analysis to documenting or incrementally improving the current process. Working Style
• Focuses on business value and usable outcomes rather than methodology compliance.
• Creates clarity from ambiguity, applies enough structure to keep teams aligned, and adapts plans as evidence and constraints change.
• Asks precise questions, tests assumptions, and distinguishes a stated preference from a true business requirement.
• Works comfortably across executive, operational, and engineering conversations and takes ownership from process design through a capability that works in the client's environment.

Pay:

$75.00 - $100.00 per hour Expected hours: No more than 40.0 per week

Work Location:

Hybrid remote in McKinney, TX 75070