Principal, Machine Learning Software Engineer, Admin Central

Workday • Pleasanton, CA

2d • $190,600 - $342,000 • Hybrid

About The Position

As a Principal Software Engineer (ML/AI) on Workday’s Admin Central team, you will lead the architecture and implementation of next-generation AI platforms and autonomous agent frameworks. The role sits at the intersection of machine learning, event-driven data systems, and enterprise platform engineering, translating AI research into reliable production systems handling tens of millions of daily requests across enterprise tenants.

You will design ML infrastructure, multi-agent orchestration layers, and highly available usage pipelines that support enterprise decision-making, usage tracking, and automatic tenant maintenance. The role includes technical leadership and partnership with software engineering, Product Management, Data Engineering, SRE, and Legal/Compliance stakeholders to turn business needs into scalable technical designs and data-governance strategies.

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 to multi-agent coordination, intent classification, and workflow optimization.
• Experience with MCP integrations and tool-use frameworks.
• Proven ability to lead exploratory data analysis on multi-tenant agentic workflows and shape data strategy.
• Mastery of high-dimensional embeddings, vector database management, and data isolation.
• Experience with Kubernetes and Docker deployment, automated CI/CD retraining, and managing model drift and latency at scale.
• Mastery of Python and the ML ecosystem, including PyTorch, TensorFlow, LangChain, LangSmith, LlamaIndex, NumPy, Pandas, and Scikit-learn.
• Strong experience deploying production systems with PostgreSQL, Redis, Kafka, and cloud infrastructure such as AWS, GCP, or Azure.
• Exceptional collaboration and mentoring skills, including technical leadership of cross-functional pods and sprint planning.
• 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.

Responsibilities

• Design, implement, and maintain agentic AI 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, and cloud-native technologies.
• Architect multi-tenant runtimes that deliver 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.
• Ensure AI systems are explainable, secure, and resilient in production.
• Partner with software engineers, Product Managers, Data Engineering, SRE, and Legal/Compliance stakeholders to develop scalable technical designs and long-term data-governance strategies.
• Technically lead cross-functional pods, drive sprint planning, and communicate technical and governance decisions to executives.
• Lead exploratory data analysis on multi-tenant agentic workflows to inform data strategy.
• Lead model building, fine-tuning, and deployment of domain-specific foundation models, including automated CI/CD retraining and management of model drift and latency.

Benefits

• May be eligible for the Workday Bonus Plan or a role-specific commission or bonus.
• May be eligible for annual refresh stock grants.
• Comprehensive benefits are referenced, but specific benefits are not listed in the posting.
• Flexible work schedule, with at least 50% of each quarter spent in the office or in the field with customers, prospects, and partners, depending on role.

What This Job Offers

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