AI Transformation Manager

Job Description & Summary The opportunity Convert business priorities into high-value AI products and agentic workflows, owning discovery, process redesign, product direction, agile backlog and benefits realization. What you will be doing · Lead value-discovery and process-design workshops with business and technology stakeholders. · Map current workflows, decisions, hand-offs, pain points, controls and performance baselines. · Prioritize agentic use cases based on value, feasibility, risk and time to impact. · Act as product owner or product-management lead for client delivery, maintaining outcomes, roadmap and backlog. · Define business cases, KPIs, benefit owners and measurement approaches. · Coordinate user adoption, operating-model changes and transition to business ownership. What we need from you · 7+ years in management consulting, digital transformation, product management or process improvement. · Strong experience in business cases, process redesign, agile delivery and executive facilitation. · Ability to translate business needs into clear product outcomes and acceptance criteria. · Working understanding of AI, agents, data dependencies, human oversight and automation. Relevant AI technologies and tooling · Working knowledge of agentic solution concepts, including tool calling, workflow orchestration, memory, retrieval-augmented generation, human-in-the-loop controls, evaluation and observability. · Ability to convert a business process into agent roles, tools, decision points, structured inputs and outputs, exception paths, acceptance criteria and measurable value hypotheses. · Familiarity with platforms and frameworks used by delivery teams, such as LangChain and LangGraph, Microsoft Agent Framework or Semantic Kernel, OpenAI Agents SDK, Microsoft Copilot Studio and workflow automation platforms. · Experience using Agile product-management tooling such as Azure DevOps or Jira to manage epics, user stories, acceptance criteria, dependencies, releases and benefits measures. Measures of success · Value of prioritized use cases · Backlog quality and stakeholder alignment · Speed from discovery to usable release · Benefits measured after deployment · Client adoption and satisfaction Key interfaces · Other members of the AI Transformation & Agentic Systems Practice · PwC sector, functional, cloud, cyber, risk, Responsible AI and change specialists · Client business owners, product owners, technology teams and operational users · Technology alliance and implementation partners where relevant Contribution to the practice · Support proposals, client workshops and market development appropriate to seniority. · Contribute reusable methods, patterns, code, assets and lessons learned. · Coach colleagues and participate in the capability’s continuous learning agenda. · Uphold PwC quality, independence, confidentiality and risk-management requirements. #LI-BS1 #LI-Hybrid