Abhi.

Abhishek

Backend Engineer

NestJSNext.jsPostgreSQLMongoDBRedisQueues

2+ years building real-time systems, AI-integrated backends, and async workflows. Most of what I've built has gone into production and stayed there.

Platforms in production ·Healthcare ·EdTech ·Hiring-Tech ·Mithila Stack

Where I've worked

March 2024 - Present

Mithila Stack

Backend Engineer

Working on the backend of multiple production systems across different domains — hiring-tech, healthtech, edtech, and food-tech.

Built and shipped four products from scratch — Meleys (AI interview and assessment platform), MARS (medication adherence platform with AI-driven patient follow-ups), iPariksha (online examination system with automated evaluation), and Foodam (a city-level tiffin and food ordering service). Owned the backend end to end on all of them — API design, database, async workflows, third-party integrations, and deployment.

Day to day I work with Node.js, NestJS, Express.js, Fastify, PostgreSQL, MongoDB, Redis, and BullMQ. Most of the work has involved real-time systems, background job processing, and integrating AI services into practical workflows.

Handle deployment and infrastructure using Docker and Jenkins CI/CD pipelines on AWS. Work with HIPAA-compliant infrastructure for healthcare applications, managing sensitive PHI data with proper security controls and isolated services.

Backend

Node.jsNestJSExpress.jsFastifyPostgreSQLMongoDBRedisBullMQ

DevOps & Cloud

DockerJenkinsAWSCI/CDLinux

Frontend

Next.jsReactTypeScriptTailwind CSS

Platforms I've built. All in production.

01

Meleys

Hiring-Techmeleys.in

An AI-powered interview and evaluation platform with real-time proctoring. Handles candidate screening, live interviews, and automated scoring against role-specific criteria.

Built a real-time interview system with event-driven architecture for low-latency activity capture. The scoring engine evaluates candidates against custom criteria per role, and the system handles multiple concurrent sessions without performance drops.

NestJSPostgreSQLRedisBullMQWebRTCGemini AI
02

AI Clinic

Healthcareai-clinic.tech

India's default medication adherence platform with multiple AI agents working 24/7. Built multiple real-time conversational agents on LiveKit that connect hospitals with patients after surgery or discharge - monitoring recovery, delivering care instructions, and managing medication schedules. Integrated with MARS system to support hospital internal operations.

Architected a multi-agent system on LiveKit for real-time patient engagement across multiple hospitals. Each agent handles specific care moments: pre-surgery prep, medication adherence, post-surgery monitoring, prescription fulfillment, and appointment management. Hospitals can choose from multiple intervention agents based on patient needs. Integrated WhatsApp API to deliver AI doctor avatar videos for medication reminders. Built event-driven workflows with Python and Node.js for intelligent nudges. Seamlessly integrated with MARS (hospital management system) to unify patient engagement with internal workflows.

Node.jsPythonLiveKitMongoDBAzure AID-IDWhatsApp APIDockerJenkinsAWSBullMQ
03

MARS

Healthcaremars.ai-clinic.tech

Medication Adherence & Reminder System - A comprehensive hospital management platform with AI-powered patient engagement. Handles OPD operations, daily appointments, prescription management, and automated patient reminders through customizable AI agents.

Built a complete hospital management system with OPD module supporting daily appointment scheduling, prescription creation and management, and patient records. Implemented background processing for time-based, retry-safe task execution at scale. Developed an AI agent system where hospitals can select from multiple intervention agents for post-discharge patient follow-up, medication awareness, and care instruction delivery. The customized doctor avatar calls patients, delivers medication reminders with precautions, and handles follow-ups - fully automated end to end. Enforced role-based access control and secure handling of sensitive healthcare data with isolated services and scalable storage.

Node.jsMongoDBAzure AID-IDFFmpegDockerBullMQRedis
04

iPariksha

EdTechipariksha.com

An examination platform for conducting large-scale online tests with automated evaluation. Handles test creation, submission processing, result generation, and integrated payment flows.

Designed backend systems for large-scale examinations. Structured workflows for test creation, submission handling, and result generation. Integrated Razorpay payment and payout flow into the core system while maintaining reliability and enforcing clear role boundaries.

NestJSPostgreSQLRedisBullMQRazorpay
05

TiffinDost

FoodTech

A meal subscription aggregator connecting users to local kitchens for daily tiffin delivery. Handles subscription management, kitchen partnerships, and delivery coordination.

Subscription logic is deceptively tricky. Pause, resume, skip, swap kitchen - all without breaking billing state. Built with a small team and shipped to production in weeks.

TypeScriptMySQLRedisAWS EC2WebSockets

Backend engineering is about decisions, not just code.

Things break, plan for it

Queues have retries. Tasks have fallbacks. Auth has layers. I build assuming something will go wrong, because in production, it usually does.

Get the data model right first

Schema decisions shape everything else. I spend time on data models before writing routes - fixing a bad schema later costs way more.

Ship it, then make it better

A working system teaches you more than a design doc. I get something real out fast, then improve based on what actually happens.

Languages: TypeScript, JavaScript, Python

Backend: Node.js, NestJS, Fastify, Express.js

Databases: MongoDB, PostgreSQL, MySQL

Frontend: Next.js

DevOps & Cloud: Docker, Jenkins, AWS EC2, AWS S3, CI/CD, Linux

Systems: Redis, BullMQ, WebSockets, WebRTC, LiveKit, Media Processing

AI & ML: Gemini AI, Azure AI, D-ID, OpenAI, Machine Learning

Integrations: WhatsApp API, Razorpay, FFmpeg