AI Transformation Lead
Lead
Description
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.
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