Ayush Kaushik · Backend & AI Engineer

I build backend systems that stay up — and AI that actually ships.

I design and engineer production-grade APIs, LLM/RAG pipelines, and the data infrastructure behind them. Python and FastAPI at the core, with a focus on reliability, performance, and code other engineers trust.

FastAPI
production specialist
AI / RAG
LLM systems
20+
deep-dive articles

What I do

Engineering across the full backend stack

Four areas where I do my best work — usually where they overlap.

Backend Development

Robust Python/FastAPI services — 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-powered features that are grounded, evaluated, and production-ready — not demos that fall over.

  • RAG & vector search
  • LLM app integration
  • Evaluation & guardrails

Data Pipelines

Ingestion, transformation, and scheduling that move data reliably — from one-off scripts to scheduled, monitored 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

  1. Python Backend Developer

    Mar 2025 — Present

    Scalability Engineers

    Building scalable, secure backend services for the Medyx healthcare platform — APIs, async workflows, and cloud infrastructure.

  2. 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.

  3. 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

Not case-study theater — full technical breakdowns of issues I've actually debugged and shipped fixes for.

From the blog

Latest engineering writing

Working on something similar?

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