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Backend Engineer

Flowmill

Remote
Intermediate

At Flowmill, we are maniacally focused on eliminating cloud application failure by building tools that quickly and automatically pinpoint service disruption -- both caused externally from faults in cloud infrastructure and API providers, and internally from bugs and configuration errors. The underlying tech (developed at MIT) is unique in its extremely low-overhead collection and analysis, its full coverage, and its ability to be deployed in minutes with no code changes or configuration. These allow Flowmill to provide SREs and DevOps engineers with smart alerts and a complete, easy-to-read picture of their deployment -- dramatically accelerating fault resolution.

This is a chance to join a small, rockstar team with backgrounds at Facebook, Google, and VMware and change the way engineers achieve high availability and performance in their production applications.

What You’ll Do

  • Contribute into multiple components of the backend architecture of Flowmill including its custom streaming data pipeline, storage engine, and operating system-based collector technology, mostly in C/C++ as well as its customer-facing and internal APIs in Golang, time series database, and alerting logic.
  • Implement key parts of the data storage and processing infrastructure to improve horizontal scaling and fault tolerance
  • Play a key role in building and scaling out a service-based architecture

Qualifications

  • 4+ years of development experience
  • Experience building enterprise-class, performance-critical, distributed systems
  • Experience one or more general purpose programming languages such as Go, Java, Python, C/C++
  • (Highly Desired) Experience developing in C++ within the past 5 years
  • (Optional) Experience with AWS-based infrastructure, data processing with Kafka, Prometheus, Linux
Job listing has been deactivated.

Upoznaj kompaniju Flowmill

  • Flovmill dramatično ubrzava rešavanje problema sa proizvodnjom.

    Tipična primena usluga porasla je u poslednjih nekoliko godina, kako u broju usluga, tako i u broju međusobnih zavisnosti usluga. Sa ovom povećanom složenošću, trijaža neuspeha može biti efikasna samo pomoću alata za sužavanje opsega istrage.

    Praćenjem svakog para zavisnosti od usluge, Flovmill u sekundi odgovara na pitanja poput „koja je od ovih 30 usluga verovatno uzrok ovog incidenta?“, Omogućavajući eskalaciju usmerenim na manji broj relevantnijih inženjera. Ovo ubrzava trijažu, usredsređuje napore za ublažavanje i dramatično smanjuje osoblje u ratnoj sobi i sagorevanje inženjera.


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