Sr Principal AI Engineer

Workday Workday · Enterprise · Seattle, WA

Seeking a Senior Principal AI Engineer to serve as a technical architect for an AI Agent Engineering team focused on building HR & Finance AI agents. This role involves defining tooling strategy, evaluating AI frameworks, orchestrating agent workflows, and leveraging LLMs and enterprise AI technologies to design and develop scalable, reliable, and trusted AI agents. Responsibilities include architecting AI-powered agents, understanding the AI lifecycle, integrating AI tools, defining best practices for agent design, security, and governance, and developing strategies for multi-agent collaboration.

What you'd actually do

  1. Architect AI-powered agents that integrate deeply into HR and Financial workflows, accelerating intelligent decision making.
  2. Understanding of AI Lifecycle: Comprehensive knowledge of the AI system lifecycle, including problem definition, data acquisition, model training, system integration, and validation
  3. Evaluate, select, and integrate AI tools, frameworks, and platforms to ensure scalability, efficiency, and compliance
  4. Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
  5. Define best practices for agent design, security, and governance in AI-driven enterprise applications.

Skills

Required

  • Python
  • AWS
  • Azure
  • GCP
  • LLMs
  • AI agents
  • Orchestration frameworks
  • Enterprise-grade AI architectures
  • API integration
  • Large-scale automation
  • Data privacy
  • Security
  • Compliance for AI in enterprise environments

Nice to have

  • Masters/Doctorate degree in Computer Science, Mathematics, or Engineering
  • Vector databases
  • RAG
  • Fine-tuning LLMs
  • Identifying and curating datasets
  • Experimenting with models for iterative improvement

What the JD emphasized

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

Other signals

  • AI Agent Engineering team
  • architecting intelligent agents
  • technical architect for a cross-functional team building transformative AI agents
  • orchestrating agent workflows
  • leveraging LLMs, automation frameworks and enterprise AI technologies
  • design and develop scalable, reliable and trusted AI agents
  • multi-agent collaboration