2004shweta 2004shweta

Shweta Jaiswal

> Backend Engineer in progress.
> Designing APIs. Building distributed systems.
> Working with data, AI, and infrastructure.

`$ whoami`

public final class Shweta {

    private static final String ROLE =
            "Backend Engineer";

    private static final String FOCUS =
            "Scalable Backend & AI Systems";

    private static final String[] INTERESTS = {
        "Backend Engineering",
        "Distributed Systems",
        "REST APIs",
        "System Design",
        "Databases",
        "AI / RAG Systems",
        "Cloud & DevOps"
    };

    private static final String CURRENT_STACK =
            "Java + Python + PostgreSQL + Docker + AWS";

    public void execute() {
        while (true) {
            design();
            build();
            test();
            debug();
            optimize();
            learn();
        }
    }
}

`$ neofetch`

┌──────────────────────────────────────────────┐
│ SHWETA@GITHUB                                │
├──────────────────────────────────────────────┤
│ Role       : Backend Engineer                │
│ Degree     : B.Tech CSE · 2026               │
│ Focus      : Backend · AI · Distributed Sys  │
│ Languages  : Java · Python · JavaScript      │
│ Databases  : PostgreSQL · MySQL · MongoDB    │
│ Cloud      : AWS                             │
│ DevOps     : Docker · GitHub Actions         │
│ AI         : RAG · LangChain · Hugging Face  │
│ Retrieval  : BM25 · Vector Search · pgvector │
│ Messaging  : RabbitMQ                        │
│ Status     : Building & learning             │
└──────────────────────────────────────────────┘

`$ cat tech-stack`

`languages`

`backend & APIs`

REST APIs · JWT · Authentication & Authorization · API Design · Async Processing

`databases & data`

PostgreSQL · pgvector · MySQL · MongoDB · Redis · SQL · Database Indexing

`AI / LLM Engineering`

RAG · LangChain · Hugging Face · Embeddings · Vector Search · BM25

Hybrid Search · Cross-Encoder Reranking · LLM Applications · Prompt Engineering

`DevOps & Infrastructure`

Docker · Docker Compose · GitHub Actions · AWS EC2 · CI/CD · Linux

`Messaging & Distributed Systems`

RabbitMQ · Asynchronous Processing · Event-Driven Architecture · Microservices

`$ tree ./engineering`

engineering
│
├── backend
│   ├── Java
│   ├── Spring Boot
│   ├── Python
│   ├── FastAPI
│   ├── Node.js
│   ├── REST APIs
│   ├── JWT Authentication
│   └── API Design
│
├── databases
│   ├── PostgreSQL
│   ├── MySQL
│   ├── MongoDB
│   ├── Redis
│   ├── SQL Optimization
│   ├── Indexing
│   └── pgvector
│
├── ai-engineering
│   ├── RAG
│   ├── LangChain
│   ├── Hugging Face
│   ├── Embeddings
│   ├── Vector Search
│   ├── BM25
│   ├── Hybrid Retrieval
│   └── Reranking
│
├── distributed-systems
│   ├── RabbitMQ
│   ├── Async Processing
│   ├── Microservices
│   ├── Caching
│   └── Event-Driven Architecture
│
├── cloud-devops
│   ├── AWS
│   ├── EC2
│   ├── Docker
│   ├── Docker Compose
│   ├── GitHub Actions
│   ├── CI/CD
│   └── Linux
│
└── fundamentals
    ├── DSA
    ├── OOP
    ├── DBMS
    ├── Operating Systems
    ├── Computer Networks
    └── System Design

`$ git log --oneline --achievements`

2026  → Built and deployed production-oriented backend services
2026  → Built an Enterprise AI Knowledge Platform using RAG
2026  → Implemented hybrid retrieval with BM25 + vector search
2026  → Added cross-encoder reranking to improve retrieval quality
2026  → Dockerized backend applications and implemented CI/CD
2026  → Solved 300+ DSA problems
2025  → Built full-stack and backend applications
2024  → GirlScript Summer of Code Contributor
2024  → Postman API Fundamentals Student Expert
2024  → Ranked 1162 among 28,000+ GSSoC participants
....  → National-level Chess Player

`$ ./currently-learning`

$ learning --active

[██████████████████░░] System Design
[████████████████░░░░] Distributed Systems
[███████████████░░░░░] Microservices
[██████████████░░░░░░] AWS
[██████████████░░░░░░] Advanced PostgreSQL
[████████████░░░░░░░░] LLM / AI Engineering
[████████████░░░░░░░░] Backend Performance

`$ cat engineering-principles`

01. Understand the bottleneck before optimizing.

02. Prefer simple architectures until complexity is justified.

03. APIs should be predictable, observable, and maintainable.

04. Database design is part of application design.

05. Retrieval quality matters as much as generation quality.

06. Measure performance instead of guessing.

07. Build locally.
    Test automatically.
    Containerize.
    Deploy.
    Monitor.
    Improve.

`$ git status`

On branch: main

Backend        ✓
APIs           ✓
Databases      ✓
AI Engineering ✓
Docker         ✓
CI/CD          ✓
AWS            ✓
System Design  → learning

working tree: clean
mindset: always building

┌──────────────────────────────────────────────┐
│                                              │
│   build → break → debug → optimize → repeat │
│                                              │
│   Interested in backend engineering,         │
│   distributed systems and AI infrastructure. │
│                                              │
│   $ exit                                     │
│                                              │
└──────────────────────────────────────────────┘

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