Ayush Kaushik · Backend & AI Engineer

Backend systems that stay up. AI systems that ship.

I build and run production APIs, RAG pipelines, and the data infrastructure behind them. Mostly Python and FastAPI. I care about the boring things: reliability, performance, and code the next engineer can read.

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FastAPI: production specialist
AI / RAG: LLM systems
4+ yrs: running production systems

service.py running

from fastapi import FastAPI, Depends
from .rag import Retriever, answer

app = FastAPI(title="logicloop")
retriever = Retriever(top_k=5)

@app.post("/ask")
async def ask(q: str, r=Depends(retriever)):
    ctx = await r.search(q)
    return await answer(q, ctx)
    # grounded. cited. fast.

What I do

Engineering across the full backend stack

Four areas where I do my best work. The interesting projects usually need all of them.

Backend Development

Python and FastAPI services with clean architecture, async done right, and the reliability work that keeps them running at 3am.

FastAPI & async Python
SQLAlchemy & Postgres
Production hardening

API Architecture

Well-designed REST APIs that scale: versioning, auth, rate limiting, observability, and contracts your consumers can rely on.

REST & OpenAPI design
Auth & rate limiting
Caching & scaling

AI / LLM Engineering

RAG pipelines and LLM features that are grounded and evaluated. Built to survive production, not just the demo.

RAG & vector search
LLM app integration
Evaluation & guardrails

Data Pipelines

Ingestion, transformation, and scheduling that move data reliably, from one-off scripts to monitored production workflows.

ETL & ingestion
Scheduling & jobs
Cloud (GCP) automation

Experience & projects

What I've built, and where

3+ years shipping data systems, now focused on backend & AI engineering in production.

Featured project

Medyx: Healthcare Platform Backend

Python Backend Developer · Scalability Engineers

Production backend powering a healthcare platform: FastAPI services, async jobs, and a notification system, deployed and scaled on Google Cloud.

Production-grade REST APIs in FastAPI for core clinical workflows
Async services, scheduled jobs & background tasks for reliable notifications
SQLAlchemy + PostgreSQL/MySQL: schema design, migrations, query tuning
JWT/OAuth role-based auth; Firebase/FCM push with retry & failure tolerance
Deployed on GCP (Cloud Run, GKE, BigQuery) with CI/CD and observability

FastAPI SQLAlchemy PostgreSQL GCP Cloud Run Firebase/FCM CI/CD

Timeline

Python Backend Developer
Mar 2025 – Present

Scalability Engineers

Building scalable, secure backend services for the Medyx healthcare platform: APIs, async workflows, and cloud infrastructure.
Data Analyst / Data Engineer
May 2022 – Mar 2025

Scalability Engineers

BI dashboards (Qlik Sense, Power BI), optimized T-SQL, end-to-end ETL pipelines, and Python/PowerShell automation.
Author
Jan 2026 – Present

LogicLoopTech

Writing in-depth backend & AI engineering articles for developers.

B.Tech, Information Technology, Uttaranchal University

Selected work

Deep dives into real production problems

No case-study theater. These are full technical breakdowns of issues I've actually debugged and shipped fixes for.

performancedebuggingsql

FastAPI SQLAlchemy Session Leak Detection: Diagnose and Fix Long-Running DB Sessions in Production

Diagnosing a production failure that only surfaces under sustained load, and the connection-pool fix that resolved it.

Read the breakdown 02

productivitydockerdeveloper

FastAPI in Production: The Complete Deployment Guide (Docker, Workers, Scaling & Best Practices)

The full path from local development to a hardened, scalable production deployment with Docker and workers.

Read the breakdown

From the blog

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Building microservices python fastapi: design to production

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Working on something similar?

If you're building backend or AI systems and want a second set of senior eyes, let's talk.

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