Workday

4 days ago

Principal AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 16 hours agoStatus: Live

Job Summary

Design and lead the end-to-end architecture and product integration for production-grade intelligent agents. You’ll orchestrate complex agentic workflows, integrate foundation models safely into enterprise software, and champion Responsible and Governed AI for sensitive HR and financial data. Partnering with cross-functional teams, you’ll prototype, benchmark, and iterate on agent behavior while optimizing for latency, cost, and reliability as Workday scales intelligent agents for millions of users.

Location: Atlanta, Toronto, Vancouver, Boulder

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Lead end-to-end system design, architectural framework, and product integration for Workday’s next generation intelligent agents.
•Architect safe and reliable integration of foundation models into production-grade enterprise software.
•Own the design, experimentation, and orchestration of complex agentic workflows from prototype to deployment.
•Champion Responsible and Governed AI by architecting guardrails for data privacy, predictability, and explainability.
•Optimize agent-driven product constraints including latency, cost, and reliability.

Pay and Benefits

Salary: USD 217,000 - 325,000 annually

Equity and Bonus:Equity

Key Requirements

•10+ years of professional software engineering with deep expertise in distributed systems, cloud computing, and API design, plus 2+ years focused on production-grade LLM/agentic systems (or 7+ years in ML/AI with 3+ years shipping LLM-backed products).
•3+ years integrating large models (LLMs/foundation models) and modern AI APIs into user-facing enterprise products.
•2+ years designing and scaling AI orchestration architectures, including multi-agent frameworks, routing layers, and RAG pipelines.
•6+ years optimizing application performance, including API latency and user interaction design, with 2+ years applying LLM constraints like token management, cost optimization, and context-window efficiency.
•6+ years leveraging cloud platforms (e.g., AWS, GCP) to deploy scalable, responsive systems.

Experience:AILLMEnterprise softwareAgentic systems

Education:Bachelor's in Computer Science, Software Engineering, or equivalent technical field

Skills:System designHands-on executionMentorshipExperimentationCollaboration

Tech Stack:Distributed systemsCloud computingAPI designLLMsFoundation modelsAI APIsMulti-agent frameworksRouting layersRAG pipelinesAWSGCPToken managementContext-window efficiencyData privacyExplainabilityResponsible AI

Company Brief

Workday

Provides cloud-based enterprise applications for human capital management, financial management, payroll, and analytics. Delivers unified HR and finance software suites to large organizations, enabling workforce planning, talent management, payroll, and financial reporting.

Industry: HR Tech

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Pleasanton, United States

Founded: 2005

Website LinkedIn

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Workday

4 days ago

Principal AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 16 hours agoStatus: Live

Job Summary

Location: Atlanta, Toronto, Vancouver, Boulder

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Lead end-to-end system design, architectural framework, and product integration for Workday’s next generation intelligent agents.
•Architect safe and reliable integration of foundation models into production-grade enterprise software.
•Own the design, experimentation, and orchestration of complex agentic workflows from prototype to deployment.
•Champion Responsible and Governed AI by architecting guardrails for data privacy, predictability, and explainability.
•Optimize agent-driven product constraints including latency, cost, and reliability.

Pay and Benefits

Salary: USD 217,000 - 325,000 annually

Equity and Bonus:Equity

Key Requirements

•10+ years of professional software engineering with deep expertise in distributed systems, cloud computing, and API design, plus 2+ years focused on production-grade LLM/agentic systems (or 7+ years in ML/AI with 3+ years shipping LLM-backed products).
•3+ years integrating large models (LLMs/foundation models) and modern AI APIs into user-facing enterprise products.
•2+ years designing and scaling AI orchestration architectures, including multi-agent frameworks, routing layers, and RAG pipelines.
•6+ years optimizing application performance, including API latency and user interaction design, with 2+ years applying LLM constraints like token management, cost optimization, and context-window efficiency.
•6+ years leveraging cloud platforms (e.g., AWS, GCP) to deploy scalable, responsive systems.

Experience:AILLMEnterprise softwareAgentic systems

Education:Bachelor's in Computer Science, Software Engineering, or equivalent technical field

Skills:System designHands-on executionMentorshipExperimentationCollaboration

Company Brief

Workday

Industry: HR Tech

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Pleasanton, United States

Founded: 2005

Website LinkedIn