Senior Director, AI Platform Engineering – Enablement

Darum lohnt es sich

• This role requires a leader who brings deep technical knowledge of enterprise AI platforms and the strategic judgment to look across every platform EPEO offers — spanning leading AI and cloud platform providers — and define where AI belongs, what it should change, and how the organization gets there. • The Senior Director, AI Platform Engineering & Enablement brings two equally weighted mandates.

On the engineering side, this leader applies deep technical judgment to evaluate, architect, and govern how AI capabilities are integrated across EPEO’s platform portfolio — ensuring what is deployed is the right capability, properly engineered, and fit for the business functions it serves. • On the enablement side, this leader ensures AI capabilities from our major providers are not just procured but actively activated, governed, and embedded into how our platforms operate.

Requirements • 12+ years of experience in technology, including significant hands‑on platform strategy, enterprise architecture, or AI infrastructure leadership • Deep working knowledge of the enterprise AI provider landscape across leading cloud platforms, enterprise AI assistant and productivity platforms, and frontier AI model providers — able to evaluate technical capabilities and architectural fit, not just vendor positioning • Demonstrated experience assessing and rationalizing AI portfolios at enterprise scale — you have looked across a large organization’s AI landscape, identified what belongs and what doesn’t, and made recommendations that were acted on across business functions • Hands‑on background in cloud platform architecture sufficient to evaluate AI capabilities at the architectural level — not just vendor positioning • Experience designing or governing enterprise AI governance, FinOps, and enablement frameworks from the ground up — not inheriting and maintaining, but building and standing up • Strong understanding of LLM architecture, agentic patterns, RAG, multi‑model orchestration, and AI infrastructure primitives at enterprise scale • A strategically‑oriented leader who combines technical credibility with the ability to drive organizational change through influence • Proven ability to operate with a long time horizon in an environment where the technology changes quarterly — holding a multi‑year strategic view while remaining responsive to a rapidly evolving AI landscape • Experience leading in large, matrixed engineering organizations (5,000+ engineers) where influence without direct authority is the primary mode of getting things done • Genuine intellectual curiosity about the AI frontier — you follow research, engage vendors at the technical level, form independent views, and are rarely surprised by what ships • Track record of managing strategic AI vendor relationships with hyperscalers and AI‑native companies at the architecture and roadmap level • Experience in a Fortune 500 or large‑scale enterprise environment with complex regulatory, compliance, and security requirements • Demonstrated ability to build the business case for multi‑million dollar AI platform investments and present to C‑suite and board‑level stakeholders Core Competencies Demonstrates deep technical knowledge of enterprise AI platforms and cloud architecture, with a proven ability to evaluate and integrate AI capabilities across large organizations.

Combines strategic judgment with strong leadership to drive organizational change and manage complex AI vendor relationships.

Highest-signal resume keywords • Enterprise AI Platform Strategy • Cloud Platform Architecture • AI Governance Frameworks • LLM Architecture Understanding • Vendor Relationship Management ATS Optimization Keywords Hard Skills • AI Infrastructure Leadership • Enterprise Architecture • AI Portfolio Assessment • Multi‑Model Orchestration • FinOps Framework Design Soft Skills • Strategic Leadership • Influence Without Authority • Intellectual Curiosity Industry Keywords • Fortune 500 Experience • Regulatory Compliance • Security Requirements Tools & Technologies • AI Platforms • Cloud Platforms • AI Assistant Technologies