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
Timeline
-
Python Backend Developer
Mar 2025 — PresentScalability Engineers
Building scalable, secure backend services for the Medyx healthcare platform — APIs, async workflows, and cloud infrastructure.
-
Data Analyst / Data Engineer
May 2022 — Mar 2025Scalability Engineers
BI dashboards (Qlik Sense, Power BI), optimized T-SQL, end-to-end ETL pipelines, and Python/PowerShell automation.
-
Author
Jan 2026 — PresentLogicLoopTech
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.
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 resolves it.
Read the breakdown 02FastAPI 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 breakdownFrom the blog
Latest engineering writing
Mastering FastAPI Background Tasks: Real‑World Patterns, Testing, and When to Reach for Celery
Learn how to use FastAPI background tasks for email, file processing, and more. Compare built‑in BackgroundTasks with Celery, see testing tips, and get best‑practice guidelines.
Mastering FastAPI Deployment on Railway – From Docker to CI/CD
Learn step‑by‑step fastapi deployment on railway with Docker, Uvicorn workers, PostgreSQL, migrations, and GitHub Actions CI/CD in a practical guide.
Welcome to LogicLoopTech
A backend engineering blog focused on AI, RAG, FastAPI, and the real problems engineers hit in production.
Working on something similar?
If you're building backend or AI systems and want a second set of senior eyes, let's talk.