Sritej Panchumarthi

I am a Senior DevOps Engineer specializing in cloud infrastructure, DevSecOps, large-scale web platforms, AI-integrated security automation, and production-grade distributed systems. My work focuses on designing and securing highly available infrastructure that powers modern digital experiences at scale.

Over the years, I have worked extensively across AWS cloud architecture, Kubernetes, CI/CD automation, observability, platform engineering, security engineering, and edge infrastructure operations. My professional experience includes building and managing enterprise-scale systems supporting millions of users in telecommunications and digital commerce environments.

Professional Background

Currently, I work as a Senior DevOps Engineer at DISH Wireless LLC, specifically supporting Boost Mobile. DISH Wireless LLC is part of EchoStar.com, where I contribute to cloud infrastructure, production operations, automation, security, observability, and platform reliability initiatives.

My work spans multiple critical areas including:

• AWS cloud infrastructure engineering
• Kubernetes (EKS) platform operations
• DevSecOps and CI/CD automation
• Infrastructure security and IAM design
• Edge infrastructure and CDN integrations
• DNS and networking architecture
• AI-assisted code quality and security validation
• Enterprise observability and monitoring systems
• High-availability production systems
• Cloud-native application deployment strategies

I have collaborated across multiple engineering domains including platform engineering, application engineering, security, SEO, networking, CDN operations, and AI integration initiatives.

Areas of Expertise

Cloud & Infrastructure

• Amazon Web Services (AWS)
• Kubernetes / Amazon EKS
• ECS / Fargate
• EC2 and scalable compute systems
• Infrastructure as Code
• Cloud networking and routing
• CloudFront and CDN architectures
• Load balancing and edge traffic optimization

DevOps & Automation

• GitLab CI/CD pipelines
• DevSecOps workflows
• Deployment automation
• Infrastructure orchestration
• Release engineering
• Production operations
• Containerized workloads
• Docker-based build systems

Security Engineering

• IAM architecture and least-privilege access
• Security scanning automation
• Cloud security engineering
• DevSecOps security pipelines
• AI-driven code validation
• Compliance-focused engineering
• Web application security
• Infrastructure hardening

Observability & Reliability

• Dynatrace observability
• Distributed logging systems
• Metrics and monitoring pipelines
• Production debugging
• Incident response
• Performance optimization
• Reliability engineering

Research & Publications

In addition to industry engineering work, I actively contribute to technical research focused on DevSecOps, AI security integration, and machine learning security pipelines.

Published research includes:

• DevSecMLOps: A Security Framework for Machine Learning Pipelines
• Embedding Security into Pipelines: A DevSecOps Blueprint

My research interests include:

• Secure AI infrastructure
• DevSecOps automation
• AI-driven security analysis
• Cloud-native security engineering
• Scalable security architectures
• Machine learning pipeline security
• Secure CI/CD systems

Certifications

• AWS Certified Security – Specialty
• AWS Certified DevOps Engineer – Professional

These certifications reflect advanced expertise in cloud security, infrastructure automation, and large-scale AWS operational engineering.

Technical Philosophy

I strongly believe that modern infrastructure engineering should prioritize:

• Security by design
• Automation-first operations
• Scalable and resilient architectures
• Observability-driven engineering
• Cloud-native operational excellence
• Continuous improvement and innovation

My approach combines practical production engineering with forward-looking research and automation strategies.

Current Technical Interests

I continue exploring and building solutions in:

• AI-assisted infrastructure engineering
• DevSecOps platforms
• Cloud-native security systems
• Edge infrastructure optimization
• Kubernetes platform reliability
• Secure AI integration pipelines
• Intelligent observability systems
• Large-scale distributed architectures

Personal Projects

Outside of enterprise engineering work, I actively experiment with:

• Raspberry Pi infrastructure projects
• Home automation systems
• NAS and private cloud environments
• Network optimization and monitoring
• AI agent architectures
• Personal cloud and storage platforms

I enjoy building practical systems that combine security, automation, performance, and usability.

Vision

My long-term vision is to contribute to the advancement of secure, scalable, and intelligent cloud infrastructure systems that support the next generation of AI-enabled platforms and digital services.

I am particularly interested in the intersection of:

• Artificial Intelligence
• Cloud Infrastructure
• Security Engineering
• DevSecOps Automation
• Large-scale Distributed Systems