We’re not yesterday’s IT department, we're Digital Technology. The world around us keeps changing and so do we. We’re redefining what it means to be IT with a mindset centered on transformation, experience, AI-driven automation, innovation, and growth. We’re all about delivering delightful, secure customer and employee experiences that accelerate ServiceNow’s journey to become the defining enterprise software company of the 21st century. And we love co-creating, using, and highlighting our own products to do it. Ultimately, we strive to make the world work better for our employees and customers—when you work in ServiceNow Digital Technology, you work for them. The Team: The ServiceNow Enterprise Data team builds AI powered data solutions to unlock full value of Enterprise data. This means building capabilities to elevate the automation and experience to build AI-native applications and empowering everyone with Enterprise data to enable data-driven decision making for every persona in the organization.  We are looking for an experienced Technical Product Manager for Enterprise Data team, part of central Data & Analytics team. With a focus on AI, this person will lead the strategy, roadmap, and execution of data and AI platform capabilities that power next-generation intelligent enterprise applications to enable Enterprise Data for every persona and unlock full value of Enterprise data. This role focuses on building scalable, trusted, and AI-ready data infrastructure, enabling seamless integration of GenAI and Agentic AI capabilities ensuring data orchestration, model lifecycle management, and observability.This is a technical product role and expects the candidate to bring in the hands-on expertise, ensuring enterprise-grade scalability, governance, and performance while delivering customer-centric, impactful solutions that accelerate AI adoption across the organization. The ideal candidate is a strategic thinker, fast learner, adept problem-solver, and obsessed about customer value. This is a unique role to simplify the complexities for the data-world and create value with unlocking enterprise data yet keeping security as the key consideration. What you get to do in this role:  As we accelerate their AI transformation, the need for scalable, trusted, and data-rich platforms has never been greater. As a Sr Staff AI/ML Product Lead for Enterprise Data with a focus on Generative AI and Agentic AI, you will define and drive the solutions for AI-native data platform that power next-generation intelligent applications unlocking the full value of Enterprise data. In this high-impact role, you will: Own the design, solution and execution for enterprise data and GenAI platform capabilities—focusing on data lifecycle management, prompt orchestration etc Drive AI readiness and data initiatives, integrating governance, observability, and database capabilities into the data platform such as Snowflake Collaborate closely with horizontal and vertical teams to embed AI-driven capabilities and experiences into key workflows, ensuring reusability, scalability, and trust across the ecosystem. Perform research, partner with x-functional teams, users and business leads, to understand the opportunities and ideate for enterprise grade design and solutions, with a focus on scale, quality, security, and self-service across the enterprise. Prototype and validate new Agentic AI and data-driven capabilities, translating early learnings into strategic product direction. Design solutions with clarity on how users will act and create value from the data and AI models; incorporates feedback loop instrumentation into the design. Drive the adoption of products amongst the user community, increase product satisfaction and drive ACV the impact from Analytics products Combine technical depth with strategic focus, balancing innovation with operational excellence and performance optimization Champion a customer-centric and data-driven culture, promoting a deep understanding of how data, AI models and intelligence come together to drive business outcomes Influence across organizational boundaries, leading alignment between data, AI, and platform areas to ensure coherent architecture and shared innovation goals 
