Mir Sabuj
Senior Software Engineer at Casap
Dhaka, Dhaka Division, Bangladesh
Summary
🤩
Rockstar🎓
Top SchoolMir Sabuj is a Senior Software Engineer based in Dhaka with 11 years of experience building and scaling cloud-native, distributed systems using Go, Kubernetes, and microservice architectures. He has delivered production-grade platform features across fintech, collaboration, and mobility domains—most recently architecting real-time fraud and dispute automation at Casap. His background includes building managed database operators and Kubernetes tooling at AppsCode and improving cloud installability and testing at Mattermost, reflecting strong infrastructure and DevOps instincts. At Pathao and Klikit he shipped high-throughput services like dynamic pricing and in-app messaging, often optimizing resource-heavy microservices for production. Mir combines a methodical, pragmatic problem-solving style with a continuous drive to deepen technical expertise, particularly around observability and scalable service design. Colleagues know him for turning complex integration challenges into reliable, automatable systems that reduce manual work and operational risk.
10 years of coding experience
10 years of employment as a software developer
Bachelor of Science (B.Sc.), Computer Science and Engineering, 3.73, Bachelor of Science (B.Sc.), Computer Science and Engineering, 3.73 at Khulna University of Engineering and TechnologyHSC, Science, 5.00, HSC, Science, 5.00 at Notre Dame College
English, Bangla
Stackoverflow
13,759reputation
1.5mreached
211answers
51questions
docker
top-5%
alpine-linux
top-5%
go
top-5%
kubernetes
top-1%
dockerfile
top-5%
python
top-5%
Github Skills (197)
opensearch10
archiving10
nagios10
backup10
aws-s310
elasticsearch10
cloud-native10
operator10
monitoring10
kubectl10
mattermost10
golang10
database10
search-engine10
kubernetes10
Programming languages (12)
Github contributions (5)
dibyatanoy/Bengali-Handwritten-Character-Recognition-Using-Convolutional-Neural-Networks
Aug 2017 - Dec 2023
Implementation of convolutional neural networks (CNNs) of increasing complexity for classification of handwritten Bengali characters. The deepest network achieves 94.2% accuracy on test data, compared to 85.96% reported on the latest paper using CNNs for Bengali OCR.
Contributions:2 PRs in 6 years 5 months
accuracycomplexitytest-datadeep-learningcnns
aerokite/aerokite.github.io
Sep 2017 - Feb 2022
Contributions:83 pushes, 4 branches in 4 years 5 months
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