Description review

Great Question | Product Engineer | Remote (Canada) | Full-time

Great Question · Remote (Canada) · back to the listing

HR standards

36/100

poor

Title ↔ description

62/100

needs work

Reads as

Unclear

no confident match

How others title the same work

Large employers

  • Software Development Engineer, Influencer Management Adobe
  • Senior Software Engineer (EAA) Coinbase
  • Senior Software Engineer, Full Stack (Coinbase Advisor - Agentic Trading) Coinbase
  • Senior Software Engineer (Typescript), AI Clients: Duo CLI GitLab
  • Grafana Labs | Senior/Staff Software Engineer - AI / Agentic apps | 100% Remote (US + Canada) | Grafana Labs

Startups

  • Founding Software Engineer Aglide
  • Product Engineer (Founding team) Aglide
  • AiMi | Full Stack AI Engineer | Remote(Everywhere) | Full-time AiMi
  • Staff Software Engineer AiPrise
  • ALBERT | REMOTE ALMOST ANYWHERE IN THE WORLD | Hiring principal and distinguished ALBERT

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

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.

Great Question is the best way to understand your customers - whether it's mining what they've already told you, or generating new research via interviews, surveys and prototype tests. We're 2nd time founders, closed our Series A last year, with customers from Canva & Brex to Intuit & Amazon.
We're hiring product engineers to help us push the envelope on what's possible in AI engineering practices, while helping our customers bake customer insight into every product release.
You'll do well here if you have a strong sense of what makes a quality product, you're AI native, and you solve the problem of ambiguity with getting closer to customers.
We're hiring product engineers!
https://greatquestion.com/careers

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 12 points (from 48 before penalties). Reviewed 21 Sep 2026.