Principal ML Engineer, Admin Central

Workday • Pleasanton, CA

4d • $190,600 - $342,000 • Hybrid

About The Position

Workday is hiring engineers for two teams within Admin Central. Admin Central is building a unified experience for administrators across Workday, using intelligence built into the platform to transform implementations. The Business Process Optimize team develops underlying platform infrastructure, including distributed systems, high-availability usage pipelines, agentic functionality, and event-driven data flows across global product regions to support enterprise billing integrity.

In this role, the Principal Software Engineer will lead the architecture and implementation of next-generation AI platforms and autonomous agent frameworks. The work sits at the intersection of machine learning, event-driven data systems, and enterprise platform engineering, turning AI research into reliable production systems that handle tens of millions of daily requests for hundreds of enterprise tenants. The engineer will design ML infrastructure, multi-agent orchestration, and high-availability usage pipelines supporting enterprise decision-making, usage tracking, automatic tenant maintenance, and billing integrity across international regions.

The role includes technical and strategic leadership, partnering with software engineering, Product Management, Data Engineering, SRE, and Legal/Compliance stakeholders to translate business needs into scalable technical designs and data-governance strategies. Workday’s Flex Work approach combines in-person and remote work, with at least 50% of each quarter spent in an office or in the field, depending on the role. Remote home-office employees may also meet in offices for important occasions.

Requirements

• 12+ years in ML development and R&D leadership, including 8+ years with advanced ML methodologies, distributed frameworks, and cloud-based platforms, designing complex, scalable, production-grade ML systems.
• 6+ years building and hosting scalable ML services, microservices, and high-throughput production data pipelines using Java, Go, Scala, or Python.
• 4+ years working with LLMs, generative AI, RAG pipelines, and autonomous agent frameworks for real-world enterprise applications.
• Expertise in high-throughput streaming with Kafka, real-time feature extraction with Spark or Flink, and distributed columnar storage such as ClickHouse or Iceberg.
• Deep knowledge of deep learning, LLM orchestration, RAG, and agentic systems, including applying ML algorithms and Model-Based Design, MCP integrations, and tool-use frameworks to multi-agent coordination, intent classification, and workflow optimization.
• Mastery of high-dimensional embeddings, vector database management, and data isolation.
• Mastery of Python and the ML ecosystem, including PyTorch, TensorFlow, LangChain, LangSmith, LlamaIndex, NumPy, Pandas, and Scikit-learn.
• Strong experience deploying production systems on PostgreSQL, Redis, Kafka, and cloud infrastructure such as AWS, GCP, or Azure.
• Exceptional collaboration and mentoring skills, including technical leadership of cross-functional pods, sprint planning, and communicating technical and governance decisions to executives.
• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field, or equivalent experience.

Nice To Haves

• Master’s degree or PhD is strongly preferred.

Responsibilities

• Lead the architecture and implementation of next-generation AI platforms and autonomous agent frameworks.
• Design, implement, and maintain agentic capabilities, including tool calling, multi-agent workflows, long-range planning, reasoning frameworks, and human-in-the-loop integrations.
• Build secure, high-throughput REST services and event-driven data pipelines using Python, AWS, Kubernetes, and cloud-native technologies.
• Architect multi-tenant runtimes that provide fast, low-latency inference to global users.
• Establish end-to-end MLOps standards, including CI/CD automation, observability, evaluation frameworks, model monitoring, and privacy and anonymization guardrails.
• Design ML infrastructure, multi-agent orchestration layers, and high-availability usage pipelines for enterprise decision-making, usage tracking, automatic tenant maintenance, and billing integrity.
• Partner with software engineers, Product Managers, Data Engineering, SRE, and Legal/Compliance stakeholders to develop scalable technical designs and long-term data-governance strategies.
• Lead exploratory data analysis on multi-tenant agentic workflows to shape data strategy.
• Lead model building, fine-tuning, and deployment of domain-specific foundation models, including automated CI/CD retraining and management of drift and latency.
• Technically lead cross-functional pods, drive sprint planning, mentor collaborators, and communicate technical and governance decisions to executives.

Benefits

• May be eligible for the Workday Bonus Plan or a role-specific commission/bonus.
• May be eligible for annual refresh stock grants.
• Workday states that it offers comprehensive benefits; specific benefits are not listed in the posting.

What This Job Offers

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