AI Transformation Lead

Job Description & Summary The opportunity Lead the AI Transformation & Agentic Systems Practice, originate high-value client opportunities and remain accountable for commercial performance, executive relationships and the value delivered by the portfolio. What you will be doing ·        Set the practice strategy, market positioning, priority sectors and annual go-to-market agenda. ·        Build trusted relationships with boards, CEOs, COOs, CIOs and business-unit executives. ·        Lead major pursuits, executive workshops, strategic alliances and qualification decisions. ·        Sponsor complex client programs and resolve commercial, stakeholder and delivery escalations. ·        Ensure each engagement has explicit business outcomes, accountable owners and value measures. ·        Build a culture that combines consulting quality, engineering excellence, agile delivery and responsible innovation. What we need from you ·        Significant leadership experience in technology consulting, business transformation or AI-enabled change. ·        Demonstrated success originating and leading complex technology transformation engagements. ·        Strong executive communication, commercial judgment and multidisciplinary leadership. ·        Ability to connect AI, data, cloud and operating-model choices with business economics and risk. Relevant AI technologies and tooling ·        Executive-level fluency across generative AI, machine learning, agentic systems, retrieval-augmented generation, model evaluation and hybrid AI deployment, sufficient to challenge solution choices and explain their business implications. ·        Awareness of the principal agent-development ecosystems, including LangChain and LangGraph, Microsoft Agent Framework or Semantic Kernel, and OpenAI Agents SDK, together with the ability to remain vendor-neutral when shaping client propositions. ·        Understanding of AI platform economics, including model consumption, data and infrastructure costs, engineering effort, operational support and the implications of cloud, sovereign and on-premises deployment choices. Measures of success ·        Qualified pipeline and profitable revenue ·        Strategic client relationships and repeat work ·        Portfolio value realized by clients ·        Practice utilization, capability growth and retention ·        Quality and risk outcomes across engagements 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