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 Lang. Chain and Lang. Graph, 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