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      Entrevista para Senior Platform Engineer

      11 de mar. de 2026
      Candidato(a) sigiloso(a) à entrevista
      Praga
      Nenhuma oferta
      Experiência negativa
      Entrevista difícil

      Candidatura

      Candidatei-me online. Fui entrevistado pela Filevine (Praga) em mar. de 2026

      Entrevista

      Senior Platform Engineer interview process started well - the recruiter was professional and responsive. However, the technical interview revealed a major disconnect. The role combines multiple disciplines: distributed systems design (Temporal.io, long running workflows), cloud architecture, DevOps engineering (Terraform, Kubernetes, scaling, monitoring, logging, GitOps, CI/CD), and MLOps. During the interview, I realized they're looking for someone who can design complex distributed systems from scratch while also handling deep infrastructure operations. When I pointed out that these are typically separate specializations - for example, someone who designs Temporal workflows usually doesn't also configure low-level service mesh networking or write Kubernetes security policies - they disagreed with the feedback. The position has been open in Prague for 4 months with and zero hires. It's now also posted in Bratislava. The interview task (a batch transcription pipeline handling 10h+ audio files) most propably remains unsolved by any candidate. If you're considering applying, be aware that you'll need to cover both high-level system design and infrastructure operations. The fact that no one has been hired in 4 months suggests the expectations might be unrealistic.

      Perguntas de entrevista [1]

      Pergunta 1

      They asked me to design a system that processes large audio files through a pipeline of AI services. The first service only accepts a specific format, so conversion is needed. The final output is a JSON file with transcription and timestamps. The task sounds straightforward at first, but the depth they expect reveals they're looking for someone with strong distributed systems experience - handling long-running jobs, failures, retries, and scaling. It's not just about making it work, but making it reliable at scale.
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