VP of AI Platform

Zuora • Foster City, CA

6h • $271,200 - $406,800

About The Position

Zuora is seeking a Vice President of AI Platform to define and lead the strategy, architecture, and development of shared AI platform capabilities that support the company’s transition to AI-native products and operating models. The role will determine which capabilities Zuora should build, which it should adopt from the AI ecosystem, and how to create a scalable, reusable platform that enables rapid product innovation without fragmented architectures or duplicated foundational work.

The VP will work across Product, Engineering, Data, Security, and other technology leaders to turn the AI-native vision into a practical technical strategy. The role combines strategic leadership with hands-on engagement in architectural and investment decisions, building foundational capabilities that take AI applications from experimentation to production at scale. The platform will support AI-powered workflows, intelligent automation, and agentic experiences, with enterprise-grade security, reliability, governance, observability, and cost management.

The leader will also build and lead a high-impact AI platform organization, establish effective operating practices and shared development patterns, and connect platform investments to measurable customer and business outcomes. Success means providing a coherent and scalable foundation that product teams adopt to deliver reliable AI capabilities and meaningful business workflows.

Requirements

• Significant experience building and scaling platforms, infrastructure, or distributed systems in complex enterprise software environments.
• Strong understanding of modern AI architectures and the infrastructure required to support production-grade AI applications.
• Familiarity with large language models, model serving and orchestration, retrieval-augmented generation, embeddings, vector search, context engineering, and agentic application architectures.
• Experience designing systems that integrate AI capabilities with enterprise data, APIs, business logic, and transactional systems.
• Strong grounding in cloud architecture, distributed systems, security, reliability, and scalable software engineering.
• Ability to distinguish durable architectural principles from rapidly changing AI capabilities.
• Understands that AI-native software requires more than adding a model or conversational interface to an existing application.
• Thinks in terms of reusable capabilities, intelligent workflows, agents, orchestration, and systems acting on behalf of users within defined boundaries.
• Can identify which capabilities should be foundational platform services and which should remain specific to products or use cases.
• Understands the importance of context, permissions, data access, evaluation, observability, and reliability in enterprise AI workflows; maintains a practical perspective on current AI limitations and changing technology.
• Has taken complex technical initiatives from concept through architecture, development, production deployment, and scaled adoption.
• Combines strategic thinking with deep engagement in technical decisions and the ability to challenge assumptions.
• Makes clear trade-offs among speed, flexibility, cost, reliability, and long-term architectural integrity.
• Knows when to build, buy, partner, or wait for technology to mature.
• Can operate when the destination is clear but the technical and organizational path must be discovered and refined.
• Connects platform architecture and investment decisions to customer value, product differentiation, developer productivity, and commercial impact.
• Works effectively with senior Product and Engineering leaders to identify high-value AI opportunities.
• Prioritizes simplicity, reuse, and adoption over unnecessarily sophisticated infrastructure and uses measurable outcomes to evaluate platform value.
• Has experience building technology subject to demanding security, privacy, reliability, and enterprise-scale operational requirements.
• Can establish standards and governance without unnecessary bureaucracy or slowing innovation.
• Communicates complex technical concepts clearly to technical teams, product leaders, and executive stakeholders.
• Influences across organizational boundaries and builds alignment around architecture, priorities, and shared ownership.
• Attracts strong technical talent and creates an environment in which high-performing engineers can do their best work.
• Is intellectually curious, adaptable, energized by AI’s pace of change, and able to make sound decisions amid uncertainty.
• Can distinguish genuine technical opportunities from hype and establish direction without assuming every answer is known.

Responsibilities

• Define the vision, strategy, technical architecture, and roadmap for Zuora’s shared AI platform.
• Determine foundational capabilities for AI-powered products, intelligent workflows, and agentic applications across the portfolio.
• Establish a coherent architecture supporting reuse, interoperability, extensibility, and rapid product-team innovation.
• Make pragmatic build-versus-buy decisions and prioritize investments that create strategic differentiation.
• Develop shared platform capabilities so teams can incorporate AI into customer experiences and business workflows without rebuilding foundational infrastructure.
• Establish technical foundations for agents that understand intent, access context, reason through tasks, interact with enterprise systems, and take appropriate action.
• Define approaches to model integration and orchestration, context management, retrieval-augmented generation, tool use, and agent execution.
• Enable secure and reliable access to enterprise data, business logic, APIs, and transactional capabilities.
• Develop reusable patterns and services that accelerate experimentation and reduce the time to move AI from prototype to production.
• Support conventional AI-enabled experiences and increasingly autonomous, multi-step agentic workflows.
• Build a secure, reliable, scalable AI platform suited to enterprise customers and mission-critical workflows.
• Establish standards for model evaluation, testing, observability, performance, and continuous improvement.
• Manage AI quality, latency, availability, and cost, including model selection and routing.
• Partner with Security, Legal, Privacy, and Compliance teams on controls for data access, model usage, agent permissions, and execution.
• Ensure AI systems operate within authorization boundaries and include safeguards, traceability, and human oversight for consequential actions.
• Monitor production performance, identify failures, evaluate outcomes, and improve system behavior over time.
• Translate platform investments into measurable customer and business outcomes, including faster development, better experiences, greater automation, and more efficient operations.
• Set measures for platform adoption, developer productivity, reliability, AI quality, cost efficiency, and time to production.
• Prioritize investments by business impact and by the capabilities they unlock for multiple product teams.
• Communicate architectural decisions, investment priorities, trade-offs, and progress to executive leadership.
• Partner with Product and Engineering leaders to identify high-value AI opportunities and help teams rethink workflows enabled by AI.
• Establish platform interfaces, development patterns, documentation, and tools accessible to product engineers.
• Reduce duplicated infrastructure, fragmented implementations, and unnecessary complexity across teams.
• Help define the operating model for collaboration among platform engineering, AI research and application development, product management, and data teams.
• Foster rapid experimentation, disciplined engineering, and learning from production outcomes.
• Build and lead a high-caliber AI platform organization; attract and retain relevant technical talent; and establish a culture of ownership, technical excellence, accountability, and pragmatic execution.
• Develop strong cross-company partnerships and build alignment through technical credibility and clear communication of platform value.

Benefits

• Competitive compensation, variable bonus and performance-based reward opportunities, and retirement programs.
• Medical, dental, and vision insurance.
• Generous, flexible time off, paid holidays, wellness days, and a company-wide year-end break.
• Paid parental leave, including fully paid leave for eligible employees, subject to local policy.
• Learning and development stipend.
• Opportunities to volunteer and give back, including charitable donation matching where available.
• Mental wellbeing resources and support.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Education Level: No Education Listed