AI Transformation Leader

Role Summary
We are looking for a hands-on AI leader who can build and scale agentic solutions, develop high-performing teams, and drive measurable AI adoption across Commercial Excellence. This is not a strategy-only role; we need a true AI expert who has built and deployed real AI systems on a scale and can work closely with leadership to take adoption to the next level.

Role Purpose

• Partner with leadership to convert AI ambition into production-grade agent deployments and measurable business impact.
• Create reusable agent patterns, governance standards, and adoption of playbooks for engagements and delivery teams.
• Build AI depth across teams by mentoring strong practitioners and screening for true hands-on expertise.

Core Responsibilities

• Help build and deploy production-grade AI agents for business workflows such as incentive compensation, alignment, roster, commercial operations, performance management, analytics operations, and delivery productivity.
• Lead agentic solution architecture across LLM workflows, orchestration, tool usage, APIs, data pipelines, evaluation, monitoring, and feedback loops.
• Drive scaled adoption across accounts and teams with clear linkage to outcomes such as productivity, margin improvement, quality, cycle-time reduction, and better client delivery.
• Develop a high-caliber AI delivery bench, including engineers, forward deployed engineers, product SMEs, and implementation leaders.
• Establish validation frameworks, readiness gates, prompt/tooling standards, KB quality checks, and release governance to reduce rework and ensure reliability.
• Translate use cases into deployable agent solutions with measurable ROI and repeatable implementation models.
• Influence senior stakeholders, delivery teams, and product/R&D teams to embed AI into the operating model rather than treating it as isolated experimentation.

Preferred Background

• Proven AI builder-leader with hands-on experience deploying LLM/agentic systems in production at scale (not POCs), with deep expertise in agent orchestration, RAG/tooling, evaluation, and end-to-end system design.
• Strong execution + scale mindset: Drives enterprise-wide AI adoption with measurable business impact (efficiency, margin, delivery quality), operating seamlessly from code to leadership.
• High ownership talent builder: Sets a high bar, mentors teams, and can clearly distinguish real AI depth vs superficial experience while building scalable capability.
• Experience in life sciences, commercial operations, sales operations, incentive compensation, field force effectiveness, or analytics delivery is preferred.
• Experience with enterprise AI platforms, workflow automation products, knowledge-based agents, and secure client delivery environments is valuable.
• Prior experience partnering with product, engineering, delivery, and client-facing teams in a matrixed organization is helpful.