Associate DevOps Engineer • Cloud & Systems

Jay Patel

I design and automate cloud infrastructure with a focus on reliability, security, and cost efficiency. I treat cloud platforms as systems — not black boxes.

With an ICT engineering background, my interests extend into digital logic, operating systems, networking, and automation. Games influence how I think about resource planning and decision-making under constraints.

Jay Patel

Experience

Real-World Engineering Work

Hands-on experience working with production cloud infrastructure, automation pipelines, and deployment workflows in a real engineering environment.

Associate DevOps Engineer — Trainee

Wonderlend Hubs Pvt. Ltd.

Internship: Feb 2025 – Dec 2025 · Full-time Role: Jan 2026 – Present

  • • Designed and implemented a JIRA-integrated IAM automation system using Python and boto3 that processes access requests, provisions IAM users, assigns groups, applies audit tags, and updates ticket status automatically.
  • • Built secure credential delivery workflows using AWS SES and Slack notifications with enforced password resets and MFA-ready onboarding, improving access security and consistency.
  • • Supported frequent staging and production deployments across AWS-based microservices, diagnosing CI/CD pipeline failures, environment misconfigurations, and permission-related issues to unblock deployments.
  • • Collaborated with development teams to debug infrastructure and deployment issues, gaining exposure to real-world cloud failure modes and operational trade-offs.
AWSIAMPythonboto3TerraformGitLab CI/CDLinuxJIRA

Projects

Systems I’ve Built & Explored

These projects reflect my interest in cloud systems, automation, performance, and how infrastructure behaves under uncertainty, scale, and real-world constraints.

Resurge-Net — Risk-Aware Cloud Autoscaling

A research-oriented cloud autoscaling framework designed to proactively scale infrastructure by modeling demand, uncertainty, and rare workload spikes rather than reacting after SLA violations occur.

  • • Built deep demand predictors using CNN and LSTM/GRU models
  • • Trained on Alibaba Cluster Trace v2018 workload dataset
  • • Modeled mean demand, uncertainty, and spike probability
  • • Designed tunable risk-based scaling policies
  • • Demonstrated improved cost vs reliability trade-offs
Python • AWS • Time-Series Forecasting • ML Systems

DocVault — Secure Serverless Document Vault

A fully serverless document management system built to eliminate server maintenance while ensuring secure authentication, controlled access, and reproducible infrastructure deployments.

  • • AWS Lambda, API Gateway, S3, DynamoDB
  • • JWT-based authentication and authorization
  • • Presigned S3 uploads and secure file access
  • • Terraform-managed infrastructure
  • • GitLab CI/CD for Lambda, frontend, and IaC deployment

Custom CPU Design (Logisim)

A small CPU designed using Logisim to strengthen understanding of digital logic, datapaths, control units, and hardware-software interaction at the instruction level.

  • • Datapath and control unit implementation
  • • Arithmetic and logical instruction execution
  • • Instruction sequencing and execution flow
Digital Logic • ICT Foundations

Writing

Notes on Systems & Engineering

I write to clarify my thinking — about cloud infrastructure, DevOps practices, and the engineering decisions behind them.

Skills

Skills & Technical Focus

My skills are shaped by hands-on experience with real cloud infrastructure, automation workflows, and a strong foundation in core ICT and systems concepts. I focus on understanding how systems behave, not just how to configure them.

Cloud & Infrastructure

  • • AWS: IAM, EC2, S3, Lambda, API Gateway, DynamoDB, SES
  • • Serverless and cloud-native architecture patterns
  • • IAM policies, access control, and security fundamentals
  • • Cost-aware infrastructure design and trade-offs
  • • Understanding networking, compute, and storage behavior

DevOps & Automation

  • • CI/CD pipelines using GitLab CI/CD and GitHub Actions
  • • Infrastructure as Code with Terraform
  • • Docker-based containerization
  • • Linux fundamentals, debugging, and scripting
  • • Deployment troubleshooting and environment diagnostics

Backend & Cloud Applications

  • • RESTful API design and backend service development
  • • JWT-based authentication and authorization
  • • Secure file handling using presigned URLs
  • • DynamoDB and relational database fundamentals
  • • Integration of frontend applications with cloud backends

Core ICT & Systems Foundations

  • • Digital logic and basic CPU design (Logisim)
  • • Operating system fundamentals
  • • Computer networks and protocols
  • • Understanding how software maps to hardware
  • • Systems thinking over framework-driven development

Programming & Tooling

  • • Python (cloud automation, scripting, AWS tooling)
  • • C / C++ (academic and systems-level work)
  • • Shell scripting
  • • Git and collaborative development workflows

About

How I Think as an Engineer

I am an Associate DevOps Engineer with a strong interest in understanding cloud systems beyond surface-level abstractions. Rather than treating cloud platforms as black boxes, I focus on how infrastructure components interact, scale, and fail under real-world conditions.

Alongside my professional work, I am pursuing an ICT engineering degree, where my background in digital logic, operating systems, and computer networks shapes how I approach modern cloud engineering. Designing a custom CPU in Logisim helped me understand how software behavior emerges from hardware-level decisions.

Through projects like DocVault and my ongoing work on risk-aware autoscaling and microservice cost optimization on AWS, I’ve explored how automation, observability, and infrastructure design influence reliability, performance, and cost.

I also enjoy games, which influence how I think about systems from a resource and time management perspective. Games naturally involve planning under constraints, allocating limited resources, optimizing strategies over time, and responding to unexpected events — concepts that closely parallel capacity planning, autoscaling, and operational decision-making in cloud systems.

My long-term goal is to grow into a cloud and DevOps engineer who not only builds and deploys systems, but deeply understands why they behave the way they do under load, failure, and uncertainty.

Contact

Let’s Connect

Whether it’s about cloud infrastructure, DevOps roles, collaboration, or engineering discussions — feel free to reach out.