Senior AI Deployment Engineer
Your work days are brighter here.
About the Team
About the Role
Key Responsibilities
Solution Design
Strategic Advisory
Technical Leadership
Innovation & Feedback
Ecosystem Integration
VISA Sponsorship is not available for this role
Senior Level
- 5+ years of experience in enterprise software implementation, technical architecture, and technical consulting (e.g., Workday, HCM/FIN, or similar platforms), including leading complex, multi‑system initiatives
- 1+ years of hands‑on experience with enterprise AI/ML or intelligent automation deployments (e.g., LLM‑based solutions, RAG architectures, or AI‑driven workflows)
Principal Level
- 8+ years of experience in enterprise software implementation, technical architecture, and technical consulting (e.g., Workday, HCM/FIN, or similar platforms), including leading complex, multi‑system initiatives
- 2+ years of hands‑on experience with enterprise AI/ML or intelligent automation deployments (e.g., LLM‑based solutions, RAG architectures, or AI‑driven workflows)
Other Qualifications
- Strong background in
technical architecture
, with experience designing data flows, integration patterns, and security models across SaaS ecosystems and external services
- Deep familiarity with the Workday ecosystem (HCM and/or Financials), including core configuration concepts, integration frameworks, and security models, or equivalent experience with similar enterprise platforms
- Practical experience with AI concepts such as
LLMs
retrieval‑augmented generation (RAG)
, prompt design, and orchestration layers, and how these can be applied in an enterprise context
- Experience in
professional services or consulting
, leading technical delivery for high‑stakes customer programs and collaborating closely with engagement managers, functional consultants, and customer IT teams
- Excellent
communication skills
, with the ability to explain complex AI and architectural topics to non‑technical stakeholders while engaging deeply with developers, data engineers, and product teams
- Demonstrated
decision‑making
work management
skills: prioritizing technical tradeoffs, managing technical risk, and organizing complex work across multiple parallel workstreams
- Experience driving
process improvements
in technical delivery practices (e.g., establishing reference architectures, reusable patterns, or automation that improves consistency and quality)
- Strong alignment with Workday's Ethical AI principles, with a focus on designing solutions that are transparent, fair, secure, and compliant with data privacy requirements
Workday Pay Transparency Statement
spend at least half (50%) of our time each quarter in the office or in the field
Not included in the source posting: benefits.
Skills
Who can apply
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