DevOps Engineer@TOINGG , Kubernetes Practitioner
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I am a DevOps & Cloud Engineer who specialises in building production-grade, scalable, and cost-efficient systems across AWS, GCP, and Azure. I’ve delivered high-impact results in real engineering environments—deploying microservices at scale, automating deployments, implementing GitOps, and building secure CI/CD platforms that actually reduce MTTR, latency, and cloud waste.
I’ve deployed AKS clusters, architected multi-cloud platforms using Terraform, optimised data-heavy pipelines, and built end-to-end monitoring stacks with Prometheus, Grafana, and Loki. My work has cut infrastructure costs by up to 70%, reduced scraping time by 85%, improved system uptime, and enabled zero-downtime deployments through ArgoCD, blue-green, and canary rollouts.
I’ve also led engineering teams (ISRO), built distributed systems, improved API performance by 60%, and shipped MVPs for global startups. Outside work, I maintain a full DevOps lab—running Kubernetes, GitOps automation, observability stacks, and secure ingress setups on a self-hosted environment.
Engineer scalable systems, automate everything, remove inefficiencies, and deliver architectures that hold up in production—not just in demos.
Looking for roles where I can own infrastructure, optimise deployments, and help teams scale with reliability and speed.
A results-driven DevSecOps Engineer with hands-on experience designing, deploying, and optimizing scalable infrastructure across cloud, container orchestration, and CI/CD ecosystems. Proven track record building production-grade Kubernetes clusters, implementing GitOps-driven delivery, and architecting secure, cost-efficient cloud solutions across AWS, GCP, and Azure. Skilled at reducing operational overhead, improving deployment reliability, and strengthening security posture using industry-standard tooling.
At TOINGG, led critical platform engineering efforts: deployed a resilient AKS microservices architecture, managed a self-hosted MongoDB cluster with replication + sharding, implemented NGINX + Let’s Encrypt–based secure ingress layers, and delivered full observability stacks using Prometheus and Grafana — cutting MTTR by 70%. Built automated multi-environment CI/CD pipelines and rollout strategies using ArgoCD, ensuring consistent, zero-downtime deployments.
Previously at PGAGI, architected multi-cloud infrastructure with Terraform and containerized application platforms using Docker and Kubernetes. Improved data processing workflows by over 90% and integrated SonarQube and Trivy to enforce strong code quality and vulnerability controls. Delivered cost-optimized serverless architectures and reliable blue-green deployments.
As an SDE Intern at ISRO, demonstrated technical leadership by driving core feature development for Bhuvan—India’s indigenous geospatial platform—leading a 10-member engineering team, implementing multilingual support for 10+ languages, and improving geospatial rendering performance by 60%.
Pursuing a B.E. in Artificial Intelligence & Machine Learning from Dayananda Sagar College of Engineering with a 9.17 CGPA, demonstrating consistently strong academic performance. The college selected me for a prestigious ISRO internship, where I contributed to the Bhuvan geospatial platform alongside a 10-member team. This role strengthened my technical foundation in large-scale systems, multilingual application development, and geospatial data processing.
The combination of academic excellence and real-world exposure through ISRO positioned me early for high-impact engineering and DevOps roles.
