Rohan K
Software Engineer at PromptQL
Bengaluru, Karnataka, India
Summary
🤩
Rockstar🎓
Top SchoolRohan K is a software engineer based in Bengaluru with six years of experience building cloud-native backend systems and developer tooling. He has practical expertise in Kubernetes-focused workflows and DevOps, evidenced by substantive contributions to the popular Argo Workflows project improving TLS, artifact handling, GC, and CLI output. At DeepSource he designed an on-prem analysis runner and enterprise installation using Helm/Replicated and implemented custom scheduler bin-packing that cut compute costs by 11%, reflecting a strong cost-conscious infrastructure mindset. Rohan moves comfortably between backend development and operational reliability, having participated in on-call rotations and production incident mitigation. Now at PromptQL, he continues to apply his cloud-native and orchestration skills to product-focused engineering. An understated strength is his knack for refactoring and removing deprecated cruft to improve long-term maintainability of large open-source systems.
6 years of coding experience
1 year of employment as a software developer
Bachelor of Technology - BTech Computer Science, Bachelor of Technology - BTech Computer Science at Kalinga Institute of Industrial Technology, Bhubaneswar
Github Skills (12)
kubernetes10
workflow-engine10
go10
kubernetes-pods10
cicd9
devops9
docker8
http8
dockers8
cloud-native7
batch-processing7
cnc7
Programming languages (14)
Github contributions (5)
argoproj/argo-workflows
Feb 2022 - Jan 2023
Workflow Engine for Kubernetes
Role in this project:
Backend Developer & DevOps Engineer
Backend Developer & DevOps EngineerContributions:66 reviews, 45 commits, 44 PRs in 11 months
Contributions summary:Rohan primarily contributed to backend improvements and operational aspects of the Argo Workflows project. Their work included adding TLS configuration options, removing deprecated executors, refactoring code, and incorporating features like the message column in `kubectl get wf` and `argo list`. Furthermore, the user made enhancements related to artifact handling, GC, and HTTP template support. This shows a focus on improving the workflow engine's functionality and maintainability, while also touching on infrastructure aspects like artifact storage and retrieval.
workflow-automationdagworkflow-enginemachine-learninghpa
rohankmr414/anime-dl
Dec 2019 - Mar 2021
A simple command-line tool to download anime from gogoanime.
Contributions:1 review, 27 commits, 2 PRs in 1 year 3 months
command-line-tooldownloaderanime-downloadbadukgogoanime
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