Description review

CABLE | Software Engineer (early team) | Sydney, Australia (ON-SITE) | Full-time

CABLE · Sydney, Australia (ON-SITE) · back to the listing

HR standards

56/100

needs work

Title ↔ description

82/100

solid

Reads as

Full-Stack Engineer

99% confident

How others title the same work

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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

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.

We're Australia's battery-backed electricity company. We fund, install and operate batteries on-site at small businesses, then supply their power at a firm, flat rate 20–40% below incumbents, making the economics work by optimising those batteries against wholesale prices. We're live with real customers. Team of six, backed by Systemiq and Black Nova; engineering includes Casey, who previously led Google engineering in Paris and Google Maps in Sydney.
We're AI-native: engineers, energy specialists and go-to-market colleagues all ship with coding agents. Each engineer owns a product end to end, from the commercial problem through to production. Flat structure, lots of ownership.
Areas you could own:
* Customer experience: quoting, onboarding and the customer app
* Metering and billing: turning high-volume interval data into accurate bills
* Energy-market and battery data: the market, weather and telemetry pipelines behind our decisions
* The agent-driven development platform the whole team builds on
Stack: TypeScript, React, Postgres, serverless. Intro chat, system design, an agentic build, then a day with the team.
Apply at https://jobs.cable.energy/roles/3e2cd174-71f5-80ae-a1d2-db8b93f2e51d or email [email protected].

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 68 before penalties). Reviewed 2 Oct 2026.