Soham Parekh Took Multiple $200K Jobs, Did Little Work
Soham Parekh’s story is shaking Silicon Valley’s hiring foundations. The software engineer admitted to secretly working multiple full-time jobs across startups—picking up salary offers as high as $200,000 each, while contributing little to no work. In some cases, he vanished after onboarding. In others, he stayed just long enough to deliver excuses instead of code.
It started with a public warning on X (formerly Twitter) from Suhail Doshi, co-founder and former CEO of Mixpanel, who alleged that Parekh was actively deceiving startups, particularly those funded by Y Combinator (YC). The post quickly went viral, drawing similar accounts from other founders who had either hired or interviewed Parekh.
Startup leaders say Parekh aced interviews with technical brilliance and charisma, often outperforming dozens of other candidates. But once hired, his engagement would immediately falter. Reports detail a consistent pattern: missed deadlines, poor code output, and elaborate excuses—from drone strikes to visa complications and power outages. At least 10 companies hired and then fired him for similar reasons.
One of the most detailed accounts comes from Arkadiy Telegin, co-founder of AI startup Leaping AI. Impressed by Parekh’s interview performance, Telegin extended an offer of $160,000 to $200,000 with equity. Parekh agreed to start remotely from India while waiting for his U.S. O-1 visa. Shortly after onboarding, however, his performance slowed, his communication declined, and his excuses escalated. Curiously, he never sent an invoice—so no salary was paid, despite a signed agreement.
Similar experiences emerged across the startup ecosystem. Marcus Lowe, co-founder of Create, hired Parekh as a contractor with a $150,000 base. He appeared in the office for a single day before vanishing again, despite multiple start-date delays. Lowe’s investigation on GitHub revealed Parekh was contributing code to another local startup. When he visited their office, he learned the engineer was also “working” there—but was “out sick.”
Adding further intrigue, Parekh listed a master’s degree in computer science from Georgia Tech on his résumé. The university later confirmed there was no record of enrollment under his name.
Despite being outed, Parekh admitted in a podcast interview that the claims were true. He cited extreme financial hardship as the reason for holding multiple roles, working long hours, and falling behind. “I’m not proud of what I’ve done… no one really likes to work 140 hours a week. I had to do it out of necessity,” he said.
The Bigger Problem: How Startups Get Burned
Parekh’s case is less about one engineer and more about systemic weaknesses in startup hiring. Early-stage founders, racing to find elite talent in AI and engineering, often rely on fast-track hiring and trust-based contracts—especially for remote roles. This speed can compromise due diligence, allowing technically competent but unreliable candidates to slip through.
In fast-moving environments, performance often goes untracked until real damage is done. Founders told Fortune that Parekh was sometimes paid for work trials that lasted a few days, or even hours, before red flags emerged.
In one surreal instance, Telegin and a fellow YC founder discovered they had both hired Parekh without knowing—prompting the phrase: “Are we dating the same guy?” The deeper they dug, the more companies they found that had shared the same experience.
In high-stakes technical environments, this kind of deception can erode not just capital but also product timelines and team morale. Companies need stronger internal checks—not just on résumés and code commits, but on sustained engagement and delivery.
What Startups Can Learn
The Soham Parekh saga highlights a growing risk in distributed, fast-scaling tech companies: the inability to consistently track performance and enforce accountability. While trust is foundational in early-stage hiring, it should be backed by verifiable outputs.
Platforms like Teamflect—designed for performance management in remote and hybrid teams—can help founders identify drop-offs in engagement early. Unlike traditional project tools, performance systems provide structured visibility across goals, meetings, and deliverables. In cases like this, having clear KPIs and routine check-ins might have revealed inconsistencies before real losses occurred.
As the war for AI talent intensifies, especially among lean teams with tight runways, founders must reconsider their approach: speed vs. sustainability, trust vs. verification.
How can startups future-proof hiring when even the best interviewees may not show up on the job?
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