HackerRank Chakra

• Replacing a recruiter phone screen and take-home for software engineering roles with one AI-run interview that includes hands-on work
• Testing how candidates plan, use an AI coding assistant and defend their changes in a real codebase
• Running consistent first-round interviews for a high-volume or campus hiring drive
• Turning a new role's job description into a structured interview with weighted must-have skills
• Adding an AI interview stage to a Greenhouse, Workday or Ashby interview plan so invites and scores flow through the ATS
• Reviewing flagged integrity events with screenshots and recordings before advancing a candidate

Chakra's main idea is that an AI interviewer should watch candidates do the work and then question them about it, not just score how well they talk. The setup flow, evidence-linked reports and ATS hooks make it practical for teams already running high-volume technical screens, especially on HackerRank. Before you rely on it, check three things: whether the per-attempt cost beats your current screening rounds, how its scores compare with your own interviewers' scores on a pilot role, and whether your candidates and local rules are comfortable with the level of proctoring it uses.

About HackerRank Chakra

Chakra sits inside HackerRank's hiring platform as a separate AI interviewer product, alongside its Screen take-home assessments and its live Interview product. A recruiter pastes or dictates a job description, answers a few follow-up prompts (experience level, location, must-have and nice-to-have skills), and Chakra drafts an interview plan with sections, time per section, evaluation goals and sample questions. You can reorder or refocus that plan by prompting it, mark requirements as must-have so they carry more weight in scoring, and try the interview yourself as a candidate before sending invites by email, CSV upload, a shareable link, or an ATS stage. The candidate then talks with Chakra by voice. It introduces the agenda, asks planned questions, probes deeper on answers, and keeps time across sections. For coding questions it opens an in-line editor where the candidate writes and runs code, and the product page shows a canvas with a real repository and an AI coding assistant in which candidates plan and fix tickets. After the work is submitted, Chakra asks follow-up questions about the approach and trade-offs, which is the main difference from voice-only AI screeners. The report gives an overall score and per-section scores on a 5-point scale, a summary of strengths and gaps, bullet points linked to timestamped transcript evidence, a full screen and webcam recording with a synced transcript, and a list of integrity flags with screenshots or webcam images. Integrity checks cover full-screen exits, extra monitors, missing or extra faces, phones and tablets on camera, and screenshots that show unauthorized tools; an optional Windows and macOS desktop app adds a locked-down mode that blocks other apps, screen sharing, VMs and copy-paste. HackerRank's AI features page says the interview-creation and live interviewer agents run on Anthropic Claude and the reporting agent on OpenAI. Documented integrations cover Greenhouse, Workday and Ashby, HackerRank's blog also names Eightfold, and there is an API for reports plus a Chakra MCP server. The trade-offs: HackerRank says pricing is per interview attempt with volume discounts but does not publish rates, candidates must accept webcam, microphone and screen monitoring, and the scoring-accuracy and fairness work described on the product page is HackerRank's own account. Chakra produces scores and recommendations; per HackerRank's CEO in TechCrunch, the hiring decision stays with people.