Senior Principal Architect, AI Platform

Workday • Pleasanton, CA

2d • Hybrid

About The Position

The Senior Principal Architect is the most senior architecture leader in Workday’s AI Platform organization. This senior individual contributor owns the platform’s end-to-end architecture, defines its target state and roadmap, and ensures that the organization’s pillars build toward a coherent design. The role calls for deep expertise in distributed systems, AI platforms, model engineering, and AI governance, along with the judgment to make lasting design decisions and the ability to align teams and advise executives on technical strategy and investment.

The AI Platform provides secure, trusted, and scalable foundations for Workday, its customers, and partners to build, run, and manage AI agents across large enterprises. It governs agent operations, supports agent development and measurement, runs agents reliably at scale, manages and routes models, and provides underlying data and infrastructure.

The architect defines architecture vision, standards, and technical direction across platform services, including runtimes, orchestration, routing, model management, and data infrastructure. The position spans distributed systems reliability and scalability, model integration and optimization, AWS and GCP cloud architecture, and governance, security, privacy, compliance, auditability, and responsible AI. It also leads architecture reviews and technology evaluations, aligns teams across Workday, mentors architects and senior engineers, advises senior leadership, and represents Workday externally.

Requirements

• Bachelor’s degree in Computer Science or a related discipline.
• 15+ years of software engineering experience, including significant time in senior architecture roles.
• 8+ years defining the architecture of large-scale distributed systems running in production.
• 8+ years running architecture practices, such as reference architectures, architecture decision records, and architecture review boards.
• 5+ years architecting AI or machine-learning platforms that support production workloads at enterprise scale.
• Strong background in model engineering, including model selection, evaluation, serving, and optimization.
• Deep familiarity with large language models, their strengths and limitations, and production architecture patterns such as retrieval-augmented generation and agent orchestration.
• Strong experience with AWS and GCP architecture, including core infrastructure and managed AI services.
• Working knowledge of enterprise AI governance, including security, privacy, compliance, and responsible AI practices.
• Ability to set architectural direction and influence multiple teams without direct authority.
• Excellent communication skills, including explaining complex architecture to executives and engaging deeply with engineers.
• Track record of mentoring architects and senior engineers.
• Sound judgment in balancing innovation against platform stability, cost, and risk.

Nice To Haves

• Experience with agent frameworks and interaction protocols such as LangGraph, MCP, and A2A.
• Experience architecting container and orchestration platforms such as Kubernetes at scale.
• Familiarity with AI regulation and data sovereignty requirements, such as the EU AI Act.
• Recognized technical reputation through publications, patents, open-source contributions, or industry speaking.

Responsibilities

• Define the long-term AI Platform architecture vision, target state, and practical roadmap, aligned with business strategy and the growth of the agent ecosystem.
• Own the end-to-end architecture of platform services for agents and AI workloads, including runtimes, orchestration, routing, model management, and data infrastructure.
• Set architecture patterns and standards for highly available, large-scale distributed systems, including reliability, performance, scalability, and fault tolerance.
• Define how models are integrated, served, evaluated, and optimized, and guide tradeoffs among model quality, performance, and cost.
• Define cloud architecture across AWS and GCP, including multi-cloud design, managed AI services, and cost-effective infrastructure patterns.
• Partner with AI Governance and Sovereignty and Routing teams to incorporate governance, security, privacy, and compliance into the architecture; support auditability, responsible AI, and evolving regulatory requirements.
• Establish reference architectures, design patterns, and architecture principles; lead architecture reviews and make or guide critical design decisions.
• Lead evaluation of frameworks, platforms, and vendors, including build-versus-buy decisions, with a focus on long-term architectural fit.
• Align with all AI Platform pillars and Workday architects on shared standards, design conflicts, and integration with Workday products.
• Mentor architects and senior engineers, raise the organization’s design bar, and build an architecture community.
• Advise senior leadership on architecture strategy, technical risk, and investment tradeoffs.
• Represent Workday through industry partnerships, standards bodies, open-source communities, and conferences.

Benefits

• May be eligible for the Workday Bonus Plan or a role-specific commission/bonus.
• May receive annual refresh stock grants.
• Comprehensive benefits are referenced; specific benefits are not listed in the posting.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal