Available for Full-Time Roles

Hello, I'm
Aashish Gajadhane

Software Engineer

Building software that's reliable, scalable, and built for production.

Mumbai, India

Focus Areas

Distributed Backend Systems

High-throughput APIs, worker orchestration, & scalable microservices.

Enterprise RAG & AI Infrastructure

Production AI workflows, vector retrieval pipelines, & LLM orchestration.

Event-Driven Architectures

Decoupled workers, queue-backed async processing, & SSE progress streaming.

I build reliable systems for modern AI products.

My work is less about calling LLM APIs and more about designing the infrastructure around them: asynchronous processing, distributed workers, retrieval systems, event-driven pipelines, and backend architectures that remain reliable under production workloads.

Whether it's an enterprise RAG platform, an AI media generation pipeline, or a real-time backend service, I like understanding the constraints first and then designing systems that scale with the product.

Beyond code

When I’m away from the keyboard, you’ll usually find me on a motorbike, riding through the ghats of Maharashtra or along the Konkan coast with my Wife🫰🏻 or the Boys.

Systems Thinking

I design around bottlenecks, failure modes, and scale before writing code.

Event-Driven Architecture

I prefer asynchronous workflows, queues, and loosely coupled services over blocking request chains.

Production Mindset

Reliability, observability, and recoverability matter just as much as shipping features.

Engineering Experience

A few of the production systems I've worked on over the past few years.

Backend & AI Systems Consultant (Contract)

Current
CoreComAI
Remote
Present

Built the backend architecture for an AI media generation platform that transforms product catalogs into marketing-ready images and videos. My work focused on distributed worker orchestration, GPU inference pipelines, asynchronous job execution, and designing a system that could scale reliably under long-running media workloads.

FastAPIARQOpenAIRedisPostgreSQLFFmpegRunPodReact.js
  • Event-driven pipeline using FastAPI, ARQ, Redis, PostgreSQL, RunPod, and SSE.
  • Dedicated FFmpeg worker pool separating CPU-bound rendering from GPU inference.
  • Configurable concurrency, retries, and stage isolation for reliable execution.
  • Structured logging and job lifecycle tracking across distributed workers.

Software Development Engineer

Troopr Labs
Remote
August 2025 – February 2026

Worked on the backend systems powering an enterprise AI assistant platform used by 100k+ users. My work centered around knowledge retrieval, event-driven automation, and building internal tooling that enabled non-technical teams to manage enterprise documentation.

Node.jsLangChainAWS BedrockBullMQMongoDBVectorDB
  • Built Slack & Teams-triggered RAG workflows.
  • Developed a multi-tenant Help Center platform with a real-time editor and live preview.
  • Improved retrieval quality through prompt and search refinements.
  • Integrated MongoDB Atlas Vector Search with LangChain and AWS Bedrock.

Full-Stack Engineer (Contract)

SEEme Inc
Mumbai
March 2025 – August 2025

Built the media processing infrastructure behind a production social platform, focusing on adaptive video streaming, backend performance, and asynchronous processing.

Node.jsMongoDBAWS LambdaWebsocketsS3HLS
  • Event-driven HLS processing pipeline using S3 upload triggers and Lambda transcoders.
  • Reduced API P95 latency by 30% via MongoDB aggregations, lean queries, and indexing.
  • Increased API throughput by parallelizing independent queries with Promise.all().
  • Delivered performance-critical backend features using Node.js, Docker, and AWS.

Backend Engineer

Plutus Labs
Remote
March 2023 – March 2025

Designed and maintained core transactional backend APIs and payment infrastructure powering creator-business collaboration workflows.

TypeScriptNode.jsStripePayPalFirebaseAWS EC2
  • Integrated Stripe and PayPal payment gateways, handling complex webhook state transitions.
  • Reduced Firebase read operations through batched retrieval strategies on high-traffic paths.
  • Managed containerized backend deployments on AWS EC2 using Docker.
  • Migrated backend codebase from JavaScript to TypeScript, enforcing strict contract typing.

Systems & Pipelines I've Shipped

View all on GitHub
AI Resume Analysis Platform

Resume Coach

Resume Coach

Distributed AI document processing pipeline with asynchronous workers, semantic vector matching, and real-time progress streaming.

Express.js & FastAPI Architecture
Cloudflare R2 payload offload
BullMQ & Redis job processing
Real-time SSE progress streaming
Built with
Node.js
Python
Redis
MongoDB
BullMQ
Non-Profit Platform

Shramika NGO

Shramika NGO

Production-grade non-profit platform built with Next.js. Achieved 100/100 Lighthouse score, custom JSON-LD schemas for global SEO reach, and integrated Razorpay donation flow driving organic international contributions within 7 days of launch.

100/100 Lighthouse performance & accessibility score
Custom JSON-LD schemas driving global reach
SEO Optimized architecture
Secure Razorpay payment gateway integration
Built with
Next.js
Bun.js
Razorpay
Cloudflare
Adaptive Streaming

Event-Driven Media Transcoding Architecture

Event-Driven Media Transcoding Architecture

Event-driven, serverless media pipeline for adaptive bitrate video streaming. Built based on the production system deployed at SEEme Inc to automate high-throughput transcoding.

Reduced API P95 latency from 6s to 3s
Event-driven serverless processing triggered by S3 uploads
Multi-resolution HLS (.m3u8) segments
Dockerized runtime environment
Built with
Node.js
AWS
Docker

Technical Deep Dives

Architecture breakdowns, engineering decisions, and lessons learned while building production systems.

ArchitectureDeep Dive8 min read

Designing a Distributed AI Media Processing Pipeline

An architectural deep dive into building CoreComAI's production media pipeline: why ARQ was chosen over BullMQ for Python workers, how decoupling CPU-bound video stitching from GPU inference solved starvation bottlenecks, 15-item batching strategies, and real-time SSE progress streaming.

FastAPIARQRedisRunPod GPUFFmpegPostgreSQLSSE
SecurityDEV.toFeatured by DEV.to
6 min read

How I Found a Fake Job Assessment Repo Hiding Malware Inside SVG Files

While auditing a take-home interview assignment, I uncovered malware hidden inside static SVG files. This write-up walks through how the exploit was structured, what it targets, and how to safely audit third-party code before running it locally.

GuideMedium
4 min read

Building Telegram Bots with Telegraf.js

A practical guide to building Telegram bots with Telegraf.js, covering architecture, environment configuration in Node.js.

The tools I build with

Technologies and systems I use to build scalable, production-ready applications.

Distributed Systems & Backend

Architecting reliable systems for scale, performance, and real-time workloads.

Node.js
TypeScript
Python
FastAPI
Go
BullMQ & ARQ
WebSockets & SSE
REST APIs

AI & Machine Learning Infrastructure

Building production-ready AI workflows and LLM-powered applications.

AWS Bedrock
RunPod GPU
LangChain
HuggingFace
Vector Embeddings
Prompt Engineering

Data & Caching

Designing data layers optimized for speed and reliability.

PostgreSQL
MongoDB
Redis
Cloudflare R2
Firebase

Infrastructure & DevOps

Deployments, automation, and cloud infrastructure at scale.

AWS
Docker
Vercel
GitHub Actions

Let's build something together

Interested in backend engineering, AI infrastructure, distributed systems, or event-driven architectures? I'd love to chat.

Currently Open To

Full-time backend & AI infrastructure rolesHigh-impact consulting & AI system designDistributed architecture projects