Senior AI Platform Architect

Workday, Inc.; Pleasanton (CA); Hybrid; USD 228,000 - 342,000; Full time

Job summary

Workday, Inc. in Pleasanton, CA, seeks a Principal Software Engineer to lead the architecture and implementation of next‑generation AI platforms and autonomous agent frameworks.

You will shape ML infrastructure, multi‑agent orchestration, and high‑availability pipelines used by tens of millions of users across enterprise tenants. You will collaborate with engineers, PMs, data teams, SRE, and compliance to deliver scalable designs, drive MLOps, and ensure secure, explainable production systems

Qualifications

• 12+ years in ML development and R&D leadership; 8+ years with advanced ML methods and scalable platforms.
• 6+ years building scalable ML services and data pipelines in production using Java, Go, Scala, or Python.
• 4+ years working with LLMs, generative AI, RAG pipelines, and autonomous agent frameworks.

Responsibilities

• Design ML infrastructure and multi-agent orchestration layers for enterprise platforms.
• Build secure, high-throughput REST services and event-driven data pipelines.
• Establish end-to-end MLOps standards including CI/CD, observability, and model monitoring.
• Lead cross-functional collaboration with engineers, PMs, data engineering, SRE, and compliance.
• Ensure explainability, security, and production resilience of AI systems.
• Mentor teams and translate governance decisions into scalable designs.

Skills

ML leadership

Distributed frameworks

Cloud platforms

Programming languages

Education

Bachelor's in CS

Master/PhD preferred

Tools

Python

AWS

Kubernetes

PostgreSQL

Redis

Kafka

Job description

Workday, Inc. in Pleasanton, CA, seeks a Principal Software Engineer to lead the architecture and implementation of next‑generation AI platforms and autonomous agent frameworks.

You will shape ML infrastructure, multi‑agent orchestration, and high‑availability pipelines used by tens of millions of users across enterprise tenants. You will collaborate with engineers, PMs, data teams, SRE, and compliance to deliver scalable designs, drive MLOps, and ensure secure, explainable production systems