Sr Principal / Principal Machine Learning Engineer

About the Role

We are seeking an experienced Senior Principal / Principal Machine Learning Engineer who will serve as a technical architect for a cross-functional team building transformative AI agents for HR & Finance. This role is critical in defining the tooling strategy, staying ahead of industry trends, and ensuring our AI-driven solutions seamlessly integrate deeply within the Workday stack. You will be responsible for evaluating and selecting AI frameworks, orchestrating agent workflows, and leveraging LLMs, automation frameworks and enterprise AI technologies to design and develop scalable, reliable and trusted AI agents for both the HR and Finance. As agents by design will span multiple parts of the business they will excel at building trusted relationships with other leaders and have experience in leading without authority and collaborating across organizational boundaries.

Key Responsibilities :

Architect AI-powered agents that integrate deeply into HR and Financial workflows, accelerating intelligent decision making.

Understanding of AI Lifecycle : Comprehensive knowledge of the AI system lifecycle, including problem definition, data acquisition, model training, system integration, and validation

Evaluate, select, and integrate AI tools, frameworks, and platforms to ensure scalability, efficiency, and compliance

Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation

Define best practices for agent design, security, and governance in AI-driven enterprise applications.

Work with product, engineering, and data science teams to design and implement AI-based automation solutions that enhance HR and financial operations.

Develop strategies for multi-agent collaboration, ensuring AI agents can work together and interact effectively with users and across the business.

Identify new opportunities to embed AI into the Workday platform.

Collaborate with external AI vendors, cloud providers, and open-source communities to bring the best-in-class technologies into our AI stack.

Establish monitoring, feedback loops, and continuous learning mechanisms to improve agent performance over time.

About You

Basic Qualifications for Sr. Principal ML Engineer

12+ years of experience with product engineering leading the development and delivery of highly available cloud products

7+ years of experience in AI, machine learning, or intelligent automation, with a focus on enterprise applications.

Deep understanding of LLMs, AI agents, and orchestration frameworks (e.g., LangGraph)

Experience with enterprise-grade AI architectures, API integration, and large-scale automation.

Proficiency in Python, cloud AI services (AWS, Azure, GCP), and AI model deployment.

Strong problem-solving skills and the ability to translate business needs into AI-powered solutions.

Experience in data privacy, security, and compliance for AI in enterprise environments

Basic Qualifications for Principal ML Engineer

10+ years of experience with product engineering leading the development and delivery of highly available cloud products

5+ years of experience in AI, machine learning, or intelligent automation, with a focus on enterprise applications.

Deep understanding of LLMs, AI agents, and orchestration frameworks (e.g., LangGraph)

Experience with enterprise-grade AI architectures, API integration, and large-scale automation.

Proficiency in Python, cloud AI services (AWS, Azure, GCP), and AI model deployment.

Strong problem-solving skills and the ability to translate business needs into AI-powered solutions.

Experience in data privacy, security, and compliance for AI in enterprise environments

Other Qualifications

Masters / Doctorate degree in a relevant field, such as Computer Science, Mathematics, or Engineering.

Experience developing and deploying machine learning solutions using large-scale datasets, including specification design, data collection and labeling, model development, validation, deployment, and ongoing monitoring.

Hands-on experience with vector databases, retrieval-augmented generation (RAG), and fine-tuning LLMs.

Experience with fine-tuning models including identifying and curating datasets as well as experimenting with models for iterative improvement

Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission / bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please .

Primary Location : USA.WA.SeattlePrimary Location Base Pay Range : $250,300 USD - $375,500 USDAdditional US Location(s) Base Pay Range : $226,500 USD - $402,000 USD

Additional Considerations :

If performed in Colorado, the pay range for this job is $238,400 - $357,600 USD based on min and max pay range for that role if performed in CO.

The application deadline for this role is the same as the posting end date stated as below :

08 / 31 / 2025