Highly skilled DevOps Engineer with 3.5 years of hands-on experience in building, automating, and managing scalable cloud infrastructure, with a strong focus on MLOps and CI/CD pipelines. Proficient in GCP, Terraform, and Kubernetes, adept at enabling Data Science teams through automated ML training pipelines. Proven ability to ensure reliable, secure, and cost-efficient deployments while continuously learning and optimizing.
Pune, Maharashtra, India
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Summary
Led DevOps initiatives at Deutsche Bank, focusing on enhancing system reliability, optimizing MLOps, and streamlining CI/CD pipelines for critical financial applications.
Highlights
Automated CI/CD pipelines using GitHub Actions, significantly enhancing system reliability and accelerating model training, testing, and deployment processes.
Designed and deployed scalable, modular infrastructure with Terraform to support machine learning environments, including setting up NVIDIA L4 GPUs on GKE for AI/ML workloads.
Migrated applications to container-native Wolfi OS images, significantly reducing image size and vulnerabilities by integrating security scanning tools like Prisma Cloud, Twistlock, and Veracode.
Deployed MLFlow on GKE for experiment tracking and model lifecycle management, enabling seamless collaboration and improving resource isolation/cost efficiency across multi-tenant clusters.
Developed and implemented a native alerting automation system using Cloud Functions and Cloud Scheduler, backed by a custom SMTP server in GKE, enhancing operational responsiveness and re-engineered SLO/SLI setups to meet business SLA requirements.
Pune, Maharashtra, India
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Summary
Contributed to cloud engineering projects at Cognizant, focusing on CI/CD pipeline optimization, infrastructure deployment, and robust monitoring solutions on GCP.
Highlights
Optimized CI/CD pipelines, significantly improving deployment efficiency and reducing production bugs by enabling more reliable and frequent code pushes.
Designed and deployed scalable cloud infrastructure on GCP using Terraform, developing TFE modules to support multi-environment landing zones for enhanced governance.
Accelerated release cycles and improved developer collaboration by implementing GitHub Actions for automated build, test, and deployment workflows.
Reduced cloud waste and improved resource utilization by building Python/Shell automation scripts for tasks like unused IP cleanup and storage bucket cost analysis.
Enhanced monitoring for Kubernetes clusters and Compute Engine VMs using Stackdriver and Prometheus, establishing proactive alerting for early issue detection and quick resolution.
Awarded By
Cognizant
Recognized for outstanding contributions and performance during tenure at Cognizant.
GCP, Google Cloud, GKE (Google Kubernetes Engine), Compute Engine, Cloud Run, Cloud Functions, Vertex AI, BigQuery, Cloud Composer, Pub/Sub, Dataflow, Dataproc, VPC, Load Balancers, Palo Alto Firewalls.
Terraform, TFE (Terraform Enterprise), Kubernetes, Docker, Ansible, GitHub Actions, CI/CD, MLflow, Prometheus, JFrog, ArgoCD, Helm, Jenkins, Istio, Composer, SonarCloud, ServiceNow.
GCP Stackdriver, Google Managed Prometheus, Cloud Logging, Alerting Systems.
Prisma Cloud, Twistlock, Veracode, IAM (Identity and Access Management), Vault, Secure Networking.
Python, Shell Scripting.
Linux, Wolfi OS.
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Summary
Designed and implemented an end-to-end CI/CD pipeline leveraging GitHub Actions and ArgoCD, integrated with SonarCloud for comprehensive quality gates. This project focused on enabling secure, automated deployments to Google Kubernetes Engine (GKE) for rapid and reliable release cycles.