Open to opportunities

Paras Mathpati

@parasmathpati

Message

I build reliable AWS and Kubernetes platforms with Terraform, CI/CD automation, and cloud-native monitoring.

India

Message

What I'm looking for

I'm looking for a cloud or DevOps role where I can build reliable AWS and Kubernetes platforms, automate infrastructure and deployments, strengthen production troubleshooting skills, and grow through hands-on work with experienced engineering teams.

I've built cloud-native AWS platforms using Terraform, Amazon EKS, ArgoCD, GitHub Actions, Prometheus, Grafana, and a Flask/PostgreSQL REST API. My work includes secure VPC architecture, IRSA, OIDC, ECR, KMS, CloudFront, and automated GitOps deployments.

At BARC, I designed a secure real-time Modbus data acquisition system for a mission-critical nuclear research environment, achieving 99.8% reliability through exception handling and data validation. At NPCIL, I architected predictive analytics pipelines for anomaly detection and operational forecasting, validating models for safety-critical enterprise datasets.

I'm currently building hands-on cloud and DevOps automation experience at Exlearn Technologies, with a focus on Linux, AWS, Docker, Kubernetes, Terraform, Jenkins, and Ansible.

Experience

Work history, roles, and key accomplishments

Current

Cloud and DevOps Intern

Current

Exlearn Technologies

Oct 2025 - Present (10 months)

Building hands-on depth in cloud architecture and DevOps automation through structured project-based training covering Networking, Linux, AWS, Docker, Kubernetes, Terraform, Jenkins, and Ansible. Working on live industry projects integrating CI/CD pipelines, containerized microservices, and cloud-native deployments on AWS.

Networking Linux AWS Docker Kubernetes Terraform Jenkins Ansible CI CD Cloud Native

Software Engineer Intern

Bhabha Atomic Research Centre

Dec 2024 - Jan 2025 (1 month)

Designed and developed a secure, real-time data acquisition system using Modbus protocol for reliable hardware-software communication in a mission-critical nuclear research environment. Implemented robust exception handling and data validation mechanisms, achieving 99.8% system reliability across continuous operation cycles.

Modbus Data Acquisition Data Validation Troubleshooting

Machine Learning Intern

NPCIL

Jun 2024 - Jul 2024 (1 month)

Architected an end-to-end predictive analytics pipeline leveraging ML algorithms for anomaly detection and operational forecasting in a nuclear energy context. Designed secure data preprocessing and feature engineering workflows optimized for model accuracy and production reliability.

Machine Learning Predictive Analytics Anomaly Detection data preprocessing Feature Engineering Model Validation

Data Analyst Intern

Aindri Initiatives

Mar 2024 - May 2024 (2 months)

Conducted trend analysis on large-scale datasets to identify market patterns and actionable business opportunities. Delivered data-driven insights using advanced statistical analysis and visualization tools, supporting strategic decision-making.

Data Analysis Trend Analysis Statistical Analysis Data Visualization