Vice President, AI & Machine Learning Engineering

Responsibilities

• Define and execute AI/ML strategy for your engineering domain, aligning research, engineering, and product delivery to ServiceNow's business objectives and revenue growth.
• Drive development and scaling of the Agentic AI Platform & Search — building foundational infrastructure for autonomous, multi-step agents that orchestrate complex, multi-department business processes with built-in governance and trust.
• Deliver omni-channel AI resolution and fulfillment, enabling seamless autonomous experiences across Chat, Voice, Computer Use, and Generative UI.
• Lead model strategy execution — including third-party and domain-specific models — optimizing for enterprise workflows at Fortune 500 scale.
• Build and operate enterprise-grade ML infrastructure: model training pipelines, feature stores, model serving, A/B experimentation, and MLOps at cloud scale.
• Lead applied research in NLP, generative AI, retrieval-augmented generation (RAG), vision, recommendation systems, and reinforcement learning for enterprise use cases.
• Partner across Platform, Data, Product, and UX teams to deliver intelligence at the right time, with the right context, in the flow of work.
• Recruit, develop, and scale a global AI/ML engineering organization of 100+ across the US, India, and Europe, cultivating a culture of research excellence and product impact.
• Represent ServiceNow as a thought leader in enterprise AI — engaging the broader AI community, supporting publications and conference participation, and helping attract world-class talent.

Qualifications

• MS or PhD in Computer Science, AI, Machine Learning, or a closely related field. Exceptional candidates with a BS and a strong industry track record will also be considered.
• 12+ years of progressive experience in AI/ML engineering and research, with 3+ years in senior leadership roles (Senior Director or VP level) at leading technology companies.
• Deep technical expertise across the modern AI stack: large language models, transformer architectures, generative AI, NLP/NLU, agentic AI systems, RAG, and reinforcement learning.
• Proven track record fine-tuning and deploying foundation models at production scale, with hands-on knowledge of distributed training, model optimization, and inference efficiency.
• Experience building and scaling ML platforms and infrastructure — including feature stores, model registries, experimentation frameworks, and CI/CD pipelines for ML systems.
• Demonstrated success shipping AI-powered products in enterprise or B2B SaaS contexts, with clear understanding of governance and trust requirements for Fortune 500 customers.
• Strong publication record or patent portfolio in top venues (NeurIPS, ICML, CVPR, ACL, KDD) and active engagement with the research community.
• Experience leading globally distributed engineering teams of 100+, with a track record of recruiting and retaining world-class AI talent.
• Strong executive presence — able to communicate AI strategy and technical vision to senior leadership, customers, and non-technical stakeholders with clarity and conviction.
• Strategic thinker with a builder's mindset, balancing long-term research investments with near-term product delivery in a fast-paced, high-growth environment.

Preferred Qualifications

• Prior Director or VP title at a major technology company or high-growth AI-native company.
• Experience with enterprise workflow platforms, knowledge management systems, or operational intelligence at scale.
• Background in building or integrating conversational AI, chatbot, or virtual agent technologies for enterprise use cases.
• Experience supporting M&A technical integration — helping absorb acquired AI teams and technology into a larger platform organization.
• Thought leadership through published research, open-source contributions, conference presentations, or advisory roles in the AI community.