AI Product
AI Solutions Architect
Between a customer who wants "AI" and a cloud bill that won't bankrupt them stands the solutions architect. This is the person sketching whiteboards: which model, which vector store, which guardrails, which inference budget.
The role is partly engineering and partly translation — taking what a business is trying to achieve and shaping it into a reference architecture that other teams can build against. Strong architects know that token economics matter as much as accuracy, and that a slow answer is often a wrong answer.
Students grow into this path by getting their hands dirty with cloud services like Vertex AI or Bedrock and learning to defend architectural choices with numbers, not vibes.
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How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
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AI Product Designer
Designing for AI means designing for uncertainty. The interface has to invite the user to ask anything, but also signal honestly when the model is guessing, hallucinating, or refusing. AI product designers shape those moments — the empty state of a chat, the disclosure on a suggestion, the gentle correction when a response is wrong. Good work here looks like an experience that feels collaborative rather than oracular, where people leave with more agency than they came in with. Students grow into this role by treating accessibility and responsible-AI questions as design problems, not compliance checks. If you care about how language, trust, and visual rhythm meet on a screen, this is fertile ground.
AI Product
AI Product Manager
Shipping an AI feature is less like launching a button and more like releasing a new colleague into the company. AI product managers decide what that colleague is good at, where it shouldn't be trusted yet, and how to measure whether it's actually helping. The work blends classic product instincts — talking to users, sequencing roadmaps — with new muscles around evaluation metrics, annotation strategy, and the economics of inference. Strong PMs in this space write crisp definitions of done that include precision and recall alongside user outcomes. Students grow into this role by learning to read a model evaluation the way they'd read a usability test: with curiosity about what the numbers are hiding.
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Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.
Skills and disciplines shown on this page are derived from the Ewance challenge catalogue. When the median annual salary is available for this role via Adzuna, it will be shown above with the sample size and country.
Portrait: Photo by Redd Francisco on Unsplash.