Description review
Workday | AI Creative Technologist | Pleasanton, CA | ONSITE | Contract
Workday · Pleasanton, CA · back to the listing
HR standards
60/100
needs work
Title ↔ description
50/100
needs work
Reads as
Machine Learning Engineer
86% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
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What the listing never says
- No section describes what the person would actually do. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
- No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
Workday's in-house creative team already uses AI every day. We built our own agent platform (Creative AI Studio) and now need a hands-on technologist to keep it running well and build what comes next.
Half the work is building: new role-specific agents, plus integrations and automations over APIs and MCP servers that move work from request to brief to production to review with fewer manual handoffs. The other half is making shipped tools work for people: supporting users, improving agents through PRs, and teaching designers and writers to get real value from them. You'll also be our technical filter on AI vendors, looking past the demo to the architecture, security, data handling, and pricing.
You'd be a good fit if you:
- Have shipped AI agents or agentic workflows that real users depend on (Claude Code, Cursor, etc.)
- Are at home in a repo: branches, PRs, code review, release hygiene
- Understand APIs, auth, webhooks, and MCP, and can map data flows before you build
- Can teach a room of non-technical creatives without jargon
Not a fit if you want to build but not support or teach, or you'd rather research AI than ship it.
To apply, email [email protected] with your resume and links or write-ups for one or two things you've built. For each one, tell me what problem it solved, how it works, and what you'd change now. I'm the hiring manager and read every one.
Half the work is building: new role-specific agents, plus integrations and automations over APIs and MCP servers that move work from request to brief to production to review with fewer manual handoffs. The other half is making shipped tools work for people: supporting users, improving agents through PRs, and teaching designers and writers to get real value from them. You'll also be our technical filter on AI vendors, looking past the demo to the architecture, security, data handling, and pricing.
You'd be a good fit if you:
- Have shipped AI agents or agentic workflows that real users depend on (Claude Code, Cursor, etc.)
- Are at home in a repo: branches, PRs, code review, release hygiene
- Understand APIs, auth, webhooks, and MCP, and can map data flows before you build
- Can teach a room of non-technical creatives without jargon
Not a fit if you want to build but not support or teach, or you'd rather research AI than ship it.
To apply, email [email protected] with your resume and links or write-ups for one or two things you've built. For each one, tell me what problem it solved, how it works, and what you'd change now. I'm the hiring manager and read every one.