Kanuri Venkat

Built and operated large-scale AWS Glue (Spark) pipelines and a governed S3 lakehouse; implemented end-to-end MLOps with SageMaker, MLflow, Kubeflow and DVC, and deployed low-latency GenAI inference platforms for real-time market data use cases.

Developed backend services and fault-tolerant cloud architectures integrating AWS Lambda, S3, SageMaker and ECS; built ETL pipelines with AWS Glue and embedded security scanning and CI/CD automation for analytics and ML workflows.

Led development of real-time monitoring platforms and GitOps deployments on EKS using ArgoCD; automated AWS infrastructure with Terraform/CloudFormation and operated serverless data lakes for analytics delivery.

Automated Kubernetes monitoring with Prometheus and Grafana, implemented CI/CD pipelines using Bitbucket and Jenkins, and managed high-availability Alertmanager clusters with Docker and Ansible.

Built scalable web platforms and containerized applications using Django, Flask and Docker; implemented CI/CD pipelines and deployed services on Kubernetes for authentication, payments and CMS features.

Completed a Post Graduate Diploma in Artificial Intelligence and Machine Learning focused on advanced ML techniques and AI systems.

Earned a Bachelor of Technology in Electronics and Communication Engineering with coursework in electronics, communications, and embedded systems.