The first person to interview you for your next job may not be a person at all. HackerRank, the coding-assessment company used by much of the tech industry, has launched Chakra, an AI interviewer built to handle the first-round screen and hand recruiters what it calls evidence-backed interview reports. TechCrunch, which covered the launch on October 5, framed it as a glimpse of what the hiring conversation is becoming.
Chakra is designed to behave less like a quiz and more like a conversation. HackerRank says it offers contextual hints in real time, raises the difficulty as a candidate succeeds, and tries to judge how someone thinks rather than only whether they reach the right answer. Alongside it the company introduced an assistant called Engage that trawls a firm's own records to rediscover past applicants who fit an open role.
Not a one-off
This is a direction, not a single product. The rival platform HackerEarth has rolled out OnScreen, an always-on AI interviewer that uses lifelike avatars and builds in identity checks and proctoring to confirm the person on the call is who they claim to be. The pitch to employers is obvious. Screening is slow, expensive and inconsistent, and a tireless machine can run a thousand first rounds a day without a diary clash.
There is an obvious irony in software interviewing the engineers who build software, and it is worth sitting with rather than laughing off. The candidate experience is the first worry. A good human interviewer reads hesitation, follows a tangent, gives someone a second chance to explain a muddled answer. Whether a model does that well, or simply rewards people who have learned to perform for it, is not yet settled.
The questions underneath
Three concerns deserve attention. One is fairness, since any system trained on past hiring can inherit the patterns in it, and a confident report can lend those patterns a false air of objectivity. Another is gaming, because once candidates know a machine is marking them, a cottage industry of coaching for the machine tends to follow. The third is consent and transparency, meaning whether applicants are clearly told a machine is assessing them and what happens to the recording.
None of this is a reason to dismiss the tools. Used for triage, with a human making the real decision, an AI interviewer could widen access by giving more applicants a fair first hearing instead of leaving CVs to rot in a pile. Used as a gatekeeper that quietly filters people out, it becomes one more opaque judgement standing between a worker and a wage. The anxiety around automated hiring is already live, as our coverage of fears about entry-level jobs showed. Handing the interview itself to a model raises the stakes, because now the machine is not just doing the work. It is deciding who gets to.
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