• Develop the vision, strategy, and technical architecture for Zuora’s AI platform, aligned with the company’s broader AI-native transformation.
• Determine the foundational capabilities required to support AI-powered products, intelligent workflows, and agentic applications across the portfolio.
• Establish a coherent platform architecture that enables reuse, interoperability, extensibility, and rapid innovation across product teams.
• Make pragmatic build-versus-buy decisions, leveraging external models, services, and infrastructure where appropriate while investing in capabilities that create strategic differentiation.
• Establish a roadmap that balances near-term product opportunities with the long-term platform capabilities required to support the company’s evolution.

Build the Foundations for AI-Native Products

• Develop shared capabilities that enable product teams to incorporate AI into customer experiences and business workflows without rebuilding foundational infrastructure for each use case.
• Establish the technical foundations for AI agents that can understand user intent, access relevant 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 required to move AI capabilities from prototype to production.
• Ensure the platform supports both conventional AI-enabled experiences and more autonomous, multi-step agentic workflows as the technology matures.

Establish Enterprise-Grade AI Infrastructure and Governance

• Build a secure, reliable, and scalable platform that meets the requirements of enterprise customers and mission-critical business workflows.
• Establish standards for model evaluation, testing, observability, performance, and continuous improvement.
• Develop approaches to managing AI quality, latency, availability, and cost, including appropriate model selection and routing.
• Partner with Security, Legal, Privacy, and Compliance teams to establish appropriate controls for data access, model usage, agent permissions, and execution.
• Ensure that AI systems operate within defined authorization boundaries, with appropriate safeguards, traceability, and human oversight for consequential actions.
• Establish mechanisms to monitor production performance, identify failures, evaluate outcomes, and improve system behavior over time.

Drive Technical and Business Outcomes

• Translate platform investments into measurable business and customer outcomes, including faster product development, improved customer experiences, increased automation, and more efficient operations.
• Establish clear measures of platform adoption, developer productivity, reliability, AI quality, cost efficiency, and time to production.
• Prioritize platform investments based on business impact and the capabilities they unlock for multiple product teams.
• Ensure the platform evolves in response to advances in AI technology, emerging customer needs, and lessons from production deployments.
• Communicate architectural decisions, investment priorities, trade-offs, and progress clearly to executive leadership.

What Success Looks Like

The VP of AI Platform will be successful when Zuora has established a coherent, secure, and scalable AI foundation that materially accelerates the company’s transition to AI-native products and operating models. Success will be reflected in:

• Faster innovation: Product teams can develop, test, and deploy AI-powered capabilities without repeatedly building foundational infrastructure.
• Production-grade AI: AI applications operate with appropriate levels of reliability, quality, security, observability, and cost control.
• Agentic capabilities: Zuora can build experiences that move beyond answering questions to executing meaningful business workflows within defined permissions.
• Platform adoption: Shared AI capabilities are used across product teams, reducing duplication and accelerating delivery.
• Customer and business value: Platform investments translate into more useful products, greater automation, and measurable improvements in customer and employee outcomes.
• A scalable technical foundation: The architecture can evolve as models, agent frameworks, and AI infrastructure continue to change.
• Organizational alignment: Product, Engineering, Data, and Security teams operate with a shared understanding of the platform strategy and how to build on it.

We are looking for a technology leader who can build the AI platform that makes Zuora’s transformation real, turning rapidly evolving AI capabilities into secure, reusable, enterprise-grade foundations that enable our products to understand intent, execute workflows, and deliver business outcomes.

Deep Technical and Architectural Expertise

• A proven technology leader with 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 capabilities that are changing rapidly as AI technology evolves.

An AI-Native Platform Mindset

• 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 that can act on behalf of users within defined boundaries.
• Can identify which capabilities should be foundational platform services and which should remain specific to individual products or use cases.
• Understands the importance of context, permissions, data access, evaluation, observability, and reliability when moving AI from demonstrations into real enterprise workflows. Maintains a practical perspective on the limitations of current AI systems and knows how to build architectures that accommodate rapid technological change.

A Builder Who Can Turn Strategy into Reality

• Has taken complex technical initiatives from initial concept through architecture, development, production deployment, and scaled adoption.
• Combines strategic thinking with the ability to engage deeply in technical decisions and challenge assumptions.
• Makes clear trade-offs between speed, flexibility, cost, reliability, and long-term architectural integrity.
• Knows when to build, when to buy, when to partner, and when to wait for the technology to mature.
• Is comfortable operating in an environment where the destination is clear but the technical and organizational path must be discovered and refined.

Strong Product and Business Orientation

• Understands that the purpose of a platform is not to build technology for its own sake, but to enable better products and business outcomes.
• Can connect 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 the highest-value opportunities for AI.
• Prioritizes simplicity, reuse, and adoption rather than building unnecessarily sophisticated infrastructure.
• Uses measurable outcomes to evaluate whether platform investments are delivering value.

Enterprise Judgment and Leadership

• Has experience building technology that must meet demanding requirements for security, privacy, reliability, and enterprise-scale operations.
• Can establish standards and governance without creating 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 where high-performing engineers can do their best work.

Comfortable Defining What Comes Next

• Is intellectually curious, adaptable, and energized by the pace of change in AI. Does not assume that established software architecture or organizational models will remain sufficient as AI capabilities evolve.
• Can separate genuine technical opportunities from hype and make sound decisions amid uncertainty.
• Brings the judgment to establish a clear direction without pretending that every answer is already known.
• Is motivated by the opportunity to help define the next generation of enterprise software platforms rather than simply operate an established one.

Enable Product and Engineering Transformation

• Partner closely with Product and Engineering leadership to identify where shared AI platform capabilities can unlock meaningful customer value and accelerate product innovation. Help product teams rethink what becomes possible when AI can interpret intent and execute workflows rather than simply respond to user commands.
• Establish clear platform interfaces, development patterns, documentation, and tools that make AI capabilities accessible to product engineers.
• Reduce duplicated infrastructure, fragmented implementations, and unnecessary complexity across teams.
• Help define the operating model for how platform engineering, AI research and application development, product management, and data teams work together.
• Foster a culture of rapid experimentation, disciplined engineering, and learning from production outcomes.

Build and Lead a High-Impact Organization

• Build a high-caliber AI platform organization that combines technical depth, strong engineering judgment, and an outcome-oriented mindset.
• Attract and retain talent across AI infrastructure, platform engineering, distributed systems, and applied AI, as appropriate to the evolving mandate.
• Establish a culture of ownership, technical excellence, accountability, and pragmatic execution. Create an environment in which teams can move quickly while maintaining the reliability, security, and discipline required for enterprise software.
• Develop strong partnerships across the company, influencing through technical credibility and a clear articulation of platform value.

Zuora offers a comprehensive total rewards package designed to support ZEOs’ wellbeing, growth, and flexibility. While specific offerings may vary by country, we typically provide:

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

*Benefits may vary by location; details will be shared during the interview process

#ZEOLife at Zuora

ZEOs (our employees) are empowered to take ownership, challenge the status quo, and make a real impact. We:

• Collaborate deeply across teams and regions
• Learn constantly and iterate often
• Build an inclusive, high-performance culture where people feel inspired, connected, and valued

Our Commitment to an Inclusive Workplace

Think, be and do you.

At Zuora, different perspectives, experiences, and contributions matter — everyone counts.

We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to (or local equivalent, where applicable).

The base pay details represent the annualized salary range for the posted position. While we share a comprehensive range, a candidate’s final base salary will fall within these guidelines and will be determined based on multiple factors including but not limited to: qualifications of the candidate, job related knowledge, prior related experience, specific and unique skills, the location of the role, internal equity and internal budget. Base pay is only one element of Zuora’s Total Rewards Package. Additional elements may also include bonus/variable compensation, equity and comprehensive benefits, more details found here .

Base Pay Details

$271,200 — $406,800 USD