The Enterprise Services and Solutions (ESS) AI and Automation Value Realization Lead is a senior leader accountable for defining and executing the AI-powered automation strategy across ESS globally.
This role is responsible for identifying, deploying, and measuring AI use cases that produce lasting, measurable business value at scale.
Operating at the intersection of enterprise AI platforms, ERP ecosystems, and business process excellence, this leader shapes how AI fundamentally changes how ESS delivers services — reducing manual effort, accelerating cycle times, and enabling self-service at a global scale.
Define and own the multi-year AI and automation strategy for ESS, spanning generative AI, retrieval-augmented generation (RAG), agentic process orchestration, NLP-driven triage, knowledge search, and self-service AI assistants.
Architect and own a rigorous benefits realization framework: baseline measurement, target-setting, attribution modeling, and validated realized value reporting for every AI initiative.
Requirements
Twelve plus years of progressive experience in AI/automation, digital transformation, or enterprise technology leadership.
Demonstrated track record designing and delivering AI solutions at scale — including RAG pipelines, LLM-powered workflows, agentic automation, or NLP-based triage systems — from proof-of-concept through production.
Hands-on experience with enterprise AI platforms and components: LLM APIs (OpenAI, Azure OpenAI, Anthropic, Gemini), vector databases (Pinecone, Azure AI Search, Weaviate, pgvector), and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent).
Deep understanding of RAG architecture — chunking strategies, embedding models, retrieval optimization, reranking, and grounded generation — and when to apply RAG vs. fine-tuning vs. prompt engineering.
Working knowledge of AI evaluation methodology: RAG evaluation metrics (faithfulness, answer relevancy, context recall), LLM output quality assessment, and red-teaming protocols.
Experience operating in complex, global, matrixed organizations with cross-functional accountability for AI governance and value delivery.
Strong financial acumen and ability to build and defend ROI models and cost-per-transaction analyses for AI investments.
Proven executive communication skills — able to represent AI strategy credibly to C-suite and board audiences.