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AI cheating in remote interviews (and how recruiters can detect it)
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AI cheating in remote interviews (and how recruiters can detect it)

25 March Online

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About this event

📅 March 25th | 🕓 4PM WEST | 🌍 Online (Crowdcast)
Sponsored by Remote Crew & Homerun

Tech hiring has changed.
Not in 5 years. Not in 2 years.
In the last 6 months.

AI copilots. Invisible voice assistants. Screen overlays. Full identity swaps.

Some candidates are simply trying to perform better.

Others are running coordinated fraud operations.

If you’re hiring engineers in 2026, this isn’t a future problem.

It’s already here.

Speakers:

Miguel Marques
Founder of Remote Crew and host of the Tech Hiring Community. Miguel brings 20 years of engineering and leadership experience to modern global hiring challenges.

Michael Kuczynski
Founder and CTO of InterviewGuard and former engineer at Amazon Web Services. He builds technical systems that solve complex, high stakes problems including AI driven interview fraud.

Ahad Abdullah
Founder of BlindSpꙨts, a browser based platform that detects and blocks hidden AI tools and proxy interviewers. BlindSpꙨts identifies invisible overlays and prevents cheating before the interview even starts.

What we'll cover:

1. Why candidates cheat

Not all cheating is equal.
We’ll talk about the two distinct motivations:

  • AI enhancement to “perform better.”
  • Organized impersonation and fraud operations

The response to each should be different.

2. How Candidates Cheat

  • AI screen overlays
  • Voice-based LLM assistance
  • Hidden browser agents
  • Identity swaps & proxy interviewers

And more...

3. Detection Strategies: What Actually Works?

We’ll compare three approaches:

  • System-Level Monitoring
  • Behavioral AI Analysis
  • Browser-Based Detection

Including trade-offs:

  • Candidate experience
  • False positives
  • Legal considerations
  • Implementation complexity

Who should attend

  • Talent Acquisition leaders
  • Technical recruiters
  • Engineering managers
  • Heads of People
  • Founders hiring remote engineers in Europe & USA

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Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

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