Glassdoor users rated their interview experience at Sherpany as 33.3% positive with a difficulty rating score of 3 out of 5 (where 5 is the highest level of difficulty). Candidates interviewing for UX Specialist and Frontend Developer rated their interviews as the hardest, whereas interviews for UX Specialist and Frontend Developer roles were rated as the easiest.
The hiring process at Sherpany takes an average of 60 days when considering 3 user submitted interviews across all job titles. Candidates applying for Frontend Developer had the quickest hiring process (on average 60 days), whereas Frontend Developer roles had the slowest hiring process (on average 60 days).
I had the first interview with Hr, it went very well. The next step was a 90-minute culture fit plus live coding. The email was detailed with what to expect, and they didn't communicate promptly, but they communicated
I applied online. I interviewed at Sherpany in Dec 2025
Interview
I was asked to complete a lengthy technical exercise that took over 10 hours. After submitting it, I received positive feedback and continued communication that suggested interest in my profile.
I was later told the role had been cancelled for “priority” reasons. Shortly after, I saw the same role reopened in a lower-cost country. When I followed up to ask for clarification, especially since I had been told I was qualified, I received no response. The role has since been opened to a blanket "Europe" location once again.
Reading other reviews here, it appears I am not the only candidate who has had this experience.
This raised serious concerns for me about how candidate time is valued, and whether extensive unpaid technical exercises are being used appropriately in the hiring process, or just exploitative. I would advise candidates to be cautious about the time commitment requested, unless they live in a lower income country. A quick look at the company’s recent hires also shows that the vast majority of roles appear to be filled there.
Interview questions [1]
Question 1
Implement a full RAG pipeline with a chat interface