Looking for a job

Yash Dhumane

@yashdhumane

Message

DevOps Engineer at Honchominds who cut change lead time by 35% and stabilized CI/CD pipelines for the Agentis platform.

India

Message

At Honchominds, I re-architected Jenkins pipelines to reduce change lead time by 35%, then migrated the Agentis platform to GitLab CI and resolved cascading pipeline failures. I also maintained a production change failure rate below 2% while reducing AWS infrastructure costs by 15%.

I’ve built and administered a self-managed 10-node Kubernetes cluster with kubeadm on Proxmox, alongside self-hosted GitLab CE and Jenkins infrastructure. Earlier, at AI Variant, I co-developed a Python and NLP resume classification engine that reduced manual screening time by 60%.

Experience

Work history, roles, and key accomplishments

Current

DevOps Engineer

Current

Honchominds

Apr 2026 - Present (5 months)

Re-architected Jenkins CI/CD pipelines using parallel builds and Docker Buildx caching, reducing change lead time by 35%. Containerized AI applications and secured Nginx/IIS gateways, enabling sub-second response delivery across 40+ languages. Automated deployment validation, rollback, and monitoring workflows, maintaining a production change failure rate below 2% while reducing AWS infrastructure

Jenkins Docker Docker Buildx Gitlab CI Nginx IIS AWS CI CD Kubernetes Django HAProxy SSL Cython Nuitka GitLab Container Registry

Web Content Executive & DevOps Associate

Future Market Insights

Aug 2025 - Apr 2026 (8 months)

Automated static asset delivery and IIS/Nginx caching configuration, improving page-load speed by 25%. Monitored production releases via centralized logging, maintaining 99.9% uptime across global platforms. Automated pre-production content validation, improving content accuracy and format consistency ahead of release.

IIS Nginx Caching Centralized Logging Monitoring Automation

Data Science & DevOps Intern

AI Variant

Jul 2024 - Oct 2024 (3 months)

Co-developed a Python/NLP resume classification engine, reducing manual resume-screening time by 60%. Containerized NLP models with Docker and deployed scalable inference endpoints on AWS.

Python NLP Docker AWS Machine Learning scikit learn