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