Posted May 25, 2026
Own the company’s AI roadmap end-to-end — from foundation model selection to business-unit-specific deployment plans:
Architect and deliver production-grade AI systems that create measurable business impact — not just prototypes:
Drive AI adoption across every business unit — making AI a core competency for the entire organization, not just the engineering team:
Design and execute a company-wide AI literacy program segmented by role: executive leadership, product managers, engineers, operations, customer-facing teams, and support functions. - Create internal AI tooling, templates, and playbooks that make it radically easy for every business unit to leverage AI capabilities (prompt libraries, no-code/low-code AI interfaces, internal copilots, AI-assisted workflows). - Establish an AI Center of Excellence that serves as the hub for best practices, reusable components, and cross-functional AI project incubation. - Implement a structured AI use-case intake and prioritization process: partner with each business unit to identify high-ROI AI opportunities, scope them properly, and execute with embedded AI support. - Build an AI talent strategy: define hiring profiles for AI engineers and applied AI roles, design technical interview processes, and develop retention programs for top AI talent. - Foster a culture of responsible AI experimentation: psychological safety to try and fail fast, coupled with rigorous post-mortems and knowledge sharing across BUs. ## What We Look For In You
10+ years in AI / deep learning, with at least 5 years in a senior leadership role (Director+ or equivalent at a top-tier tech company, high-growth startup, or leading AI lab). - Demonstrated track record of shipping production AI systems that directly impacted business outcomes at scale (revenue, engagement, efficiency). - Deep expertise across the modern AI stack: large language models, transformer architectures, RAG, fine-tuning, RLHF/DPO, prompt engineering, and agentic AI frameworks. - Strong publication record, open-source contributions, or recognized thought leadership in the AI community (conference talks, technical blog posts, courses, or widely-adopted tools). - Exceptional communication skills: ability to present complex technical concepts to board-level audiences and translate business needs into technical specifications. - Advanced degree (MS or PhD) in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field. ##
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