Why the posting itself matters here
A posting for a backend role at an infrastructure company might name Kubernetes, gRPC, and a specific consistency model, and the interview loop that follows usually probes exactly those things. A posting for a small product team might barely mention algorithms and instead emphasize shipping speed and ownership across the stack.
A candidate prepping with a generic list of coding-interview questions has no way to know which of these two realities they're actually walking into, and shows up either overprepared on the wrong thing or underprepared on the thing that actually gets asked. Reading the real posting first and practicing against its specific language closes that gap before the real interview does.
What the practice session covers
A candidate pastes in the actual posting, whether it's on the Intervieux job board or found elsewhere, and the AI interviewer builds its questions from the named stack, responsibilities, and seniority signals in that text. A posting mentioning a specific database or deployment tool gets questions grounded in that tool, not a generic system-design prompt unrelated to what the job actually involves.
The voice agent follows up on each answer in real time, so the conversation branches based on how specifically a candidate can speak to the posting's own language.
Scoring
How the scoring applies here
Scoring covers five dimensions with written reasoning behind each, and the Technical dimension here reflects how directly a candidate's answers address the posting's specific requirements, not general coding ability in the abstract.
Calibration floors and caps keep an answer that sounds technically fluent but ignores what the posting actually asked for from scoring as well as one that engages with the real requirements directly, which is the exact gap a generic interview-prep script can't catch.
Frequently asked questions
Does the posting have to be for a job on the Intervieux job board?
No. Any posting text can be pasted in, whether it's a listing on the Intervieux job board or one found on another site, since the interview type works from whatever description is supplied.
Will this ask about the specific tools named in a posting, like a particular database or framework?
Yes. Questions are built from what the posting actually names, so a listing that mentions a specific stack or tool gets questions grounded in that, rather than a generic algorithm question unrelated to the role.
How is this different from the technical interview type for software engineering?
The technical type runs a fixed style of domain-reasoning conversation regardless of any specific posting. This type reads an actual job description and shapes its questions around that listing's own requirements and stack.
Can I use this before I've formally applied to the role?
Yes. Pasting in a posting's text works whether or not an application has been submitted yet, which makes it useful for preparing ahead of applying as well as after.
What if the posting doesn't say much about the tech stack?
The AI still builds questions from whatever the posting does specify, responsibilities, seniority level, and team structure, even when the stack itself is described only loosely.
Related pages
Practice against the actual posting, not a generic script
Paste in a real software engineering job description and get questioned on its specific stack and responsibilities before the real interview does.