Product Advisor, Deployment Innovation

Workday Workday · Enterprise · USA.VA.Reston, United States +1

This role is focused on building an 'AI Deployment Engine' for Workday, which involves creating AI-powered automations and orchestrations to replace manual implementation work for HCM and Payroll projects. The core of the role is to design and refine an AI agent capable of planning work, using tools and APIs, and learning from data, utilizing technologies like RAG and LLMs.

What you'd actually do

  1. Contribute to the design and build of AI automations and orchestrations that reduce deployment effort for HCM and Payroll implementations
  2. Partner closely with some of Workday's best functional consultants to translate deployment best practices and customer nuances into robust, reusable AI-driven automations
  3. Identify opportunities to streamline and standardize implementation workflows, testing, and training content using AI tools and emerging deployment automation capabilities
  4. Collaborate with cross-functional partners across Product, Services, Customer, and Partner teams to support alignment of automation strategies with broader deployment goals
  5. Help break down ambiguous implementation challenges into scalable, tool- and workflow-based solutions that can be repeated across the ecosystem

Skills

Required

  • 5+ years of related work experience
  • Hands-on experience building automations, orchestrations, or workflow-based solutions using AI tools, scripting, or low-code/no-code platforms
  • Familiarity with AI/ML technologies such as LLMs, RAG models, MCP Servers, or similar, and a willingness to work directly with these tools to design and iterate on deployment solutions

Nice to have

  • Adaptable and open to change
  • Effective communicator and collaborator
  • Quick to learn new technologies and product areas
  • Organized and able to manage competing priorities
  • Strong analytical and problem-solving mindset
  • Comfortable using AI tools such as generative AI assistants (e.g., Cursor, Sana) to design or enhance implementation workflows, documentation, and training content
  • Familiarity with technologies like MCP Servers, RAG models, and LLMs is a plus
  • Previous consulting experience, either as an internal consultant or with a consulting or software company, is a plus

What the JD emphasized

  • AI-native talent
  • fundamentally reshape how enterprise software is deployed
  • AI-powered automations and orchestrations
  • AI agent
  • plan work, call tools and APIs
  • continuously learn from execution data
  • Model Context Protocol (MCP) Servers
  • Retrieval-Augmented Generation (RAG) models
  • LLMs
  • intelligent workflows
  • AI tools
  • generative AI assistants

Other signals

  • AI-powered automations and orchestrations
  • AI agent that operates much like a virtual implementation consultant
  • plan work, call tools and APIs
  • Retrieval-Augmented Generation (RAG) models
  • LLMs
  • intelligent workflows