user@portfolio:~$ ./welcome.sh

Hi, I'm

Jayesh Devre

>

Passionate software developer crafting scalable solutions with AWS, Azure, and Java.

class Developer {
    constructor() {
        this.passion = true;
        this.stack = ['AWS', 'Java'];
    }
}

Building reliable, scalable systems across data, AI, and cloud. No shortcuts, always production-ready. 

2024 - 2026

ARIZONA STATE UNIVERSITY

Master of Science in Information Technology

GPA: 4.00 / 4.00
2018 - 2022

SAVITRIBAI PHULE PUNE UNIVERSITY

Bachelor of Engineering in Computer Engineering

GPA: 8.56 / 10.00

Experience

What I have done so far

May 2025 — Aug 2025
May 2022 — Jul 2024
Mar 2022 — May 2022

Projects

A snapshot of systems I've shipped across backend, data, cloud, and AI.

DevOps & CI/CD2024

Distributed Voting App

DevOps-focused project: multi-service voting app with Docker, Kubernetes, and full CI/CD via GitHub Actions and Azure Pipelines.

DockerKubernetesGitHub ActionsAzure PipelinesPython.NET 7Node.jsRedisPostgreSQL

Click to flip

DevOps & CI/CD2024
  • What it demonstrates: Emphasizes DevOps - containerization, orchestration (Docker Compose, Swarm, K8s), and automated build/deploy pipelines.
  • Problem solved: Showcases production-style deployment and CI/CD for polyglot services (Python, .NET 7, Node.js) with Redis and Postgres.
  • Impact: Demonstrates end-to-end DevOps: Docker images, K8s specs, path-based CI builds, and multi-platform image pushes (GitHub Actions, Azure Pipelines).
AI Therapy Assistant2025

TherapyAI

Privacy‑focused therapy chat application with crisis detection, conversation memory, and browser‑based TTS.

Next.jsNode.jsLLM OrchestrationWebSocketsPostgreSQL

Click to flip

AI Therapy Assistant2025
  • What it demonstrates: Demonstrates ability to apply LLMs safely in a sensitive domain with guardrails.
  • Problem solved: Gives users a private, always‑available companion while escalating potential crises faster.
  • Impact: Handled intense hackathon traffic with zero downtime and won the event by shipping a polished MVP.
Personal Site2025

Developer Portfolio

High‑performance, animation‑rich portfolio showcasing backend, cloud, and AI work with responsive layout.

Next.jsTypeScriptFramer MotionVercel

Click to flip

Personal Site2025
  • What it demonstrates: Acts as a living product to showcase my UX, performance, and frontend engineering decisions.
  • Problem solved: Helps recruiters and collaborators quickly understand what I build and how I think about systems.
  • Impact: Consistently loads fast on mobile and desktop, and makes it trivial to add new case studies over time.
Async Microservice2026

ThreadBoost

Spring Boot microservice comparing blocking vs non-blocking APIs using CompletableFuture and @Async with custom thread pools.

JavaSpring BootMongoDBMavenCompletableFuture

Click to flip

Async Microservice2026
  • What it demonstrates: Demonstrates practical async programming in Spring Boot and measurable performance gains.
  • Problem solved: Shows how non-blocking endpoints improve throughput and reduce latency for CRUD and file I/O.
  • Impact: Achieved 95.6% faster CRUD workflows and 85% faster file read/write in benchmarks vs blocking approach.
ML & Cloud Pipeline2025

Heart Attack Prediction System

End-to-end ML pipeline for heart attack risk prediction using AWS EMR, SageMaker, Lambda, Athena, and SNS alerts.

PythonPySparkAWS EMRSageMakerLambdaAthenaSNSXGBoost

Click to flip

ML & Cloud Pipeline2025
  • What it demonstrates: Shows building a full ML pipeline on AWS: data processing, model training, inference, and analytics.
  • Problem solved: Processes patient vitals, trains XGBoost on SageMaker, runs real-time Lambda predictions with SNS alerts.
  • Impact: Delivers automated high-risk patient alerts and queryable analytics via Athena on processed and prediction data.
Monitoring & Analytics2023

Ops Dashboard

Operations dashboard aggregating logs, traces, and metrics into a single pane of glass for backend services.

Next.jsGrafanaPrometheusLoki

Click to flip

Monitoring & Analytics2023
  • What it demonstrates: Highlights experience building observability tools that engineers actually use during incidents.
  • Problem solved: Helps on‑call engineers see logs, metrics, and traces in one place instead of juggling tools.
  • Impact: Shortened incident investigation time by centralizing signals and adding clear SLO and release context.

Skills

Technologies and tools I work with - across parallel stacks.

Languages

JavaPythonC++JavaScriptBash

Frameworks

SpringSpring BootREST APIsJPAJWTOAuthHibernateSpring Security

Frontend & Tools

Next.jsTypeScriptReactHTMLCSSFramer MotionVercel

Cloud & DevOps

AWSAzureGCPLinuxGitGitHubKubernetesDockerTerraformJenkinsCI/CD pipelines

Database & Monitoring Tools

MySQLPostgreSQLMongoDBKafkaRedisDynatracePrometheusGrafanaPostman

Libraries

NumPyPandasTensorFlowMatplotlibscikit-learnKerasPyTorchHugging FaceMockitoJUnit

Certifications

Microsoft AZ-104Microsoft AZ-900Associate Cloud EngineerData Structures and Algorithms (Udemy)

AI in my workflow

AI is a tool. The choice about how it gets deployed is ours.

What I use:
CursorGitHub CopilotClaudeOther AI