I help startups cut cloud spend, fix backend bottlenecks and ship production-ready products — from a fixed-scope review to an end-to-end build.
My work spans a large Rails platform, Go and NestJS services, real-time systems, media processing, cloud migrations and a GitOps-managed Kubernetes fleet across AWS, GCP and Azure.
I prefer evidence over architecture theatre: find the real constraint, measure it, make the smallest useful change, and verify what moved.
The useful question is not which tools I know. It is which engineering problem I can help you make clearer.
Find the expensive workload, storage lifecycle or capacity decision instead of cutting infrastructure blindly.
Proof
Reduced video-processing infrastructure from roughly $18k/month to ~$1.8k/month and delivered additional DB, S3 and Kubernetes savings.
Move capacity decisions from guesswork to the signal that actually represents work in the system.
Proof
KEDA-scaled media workers driven by queue depth, plus seasonal capacity planning for festival-day peaks.
Design boundaries, fan-out paths and asynchronous workflows without hiding the operational cost.
Proof
Real-time messaging with Socket.IO and Redis pub/sub, plus separate Go and NestJS services around the core platform.
Change the underlying platform while keeping the product moving and the blast radius controlled.
Proof
Production migration from Azure AKS to AWS EKS with Terraform, service-by-service cutover, DNS/CDN moves and deliberate decommissioning.
Measure the slow path, make it legible, and verify that the fix improved the right thing.
Proof
Rails and Sidekiq workload tuning, OpenSearch-backed systems, CI timing splits, and New Relic / Prometheus / Grafana / Loki instrumentation.
Take an ML capability from an external black box to an operationally owned service when the economics or control justify it.
Proof
Background removal moved from a hosted vision API to a self-hosted ONNX GPU service in the Kubernetes cluster.
The strongest proof is what changed after the engineering work — cost, reliability, capacity or operational control.
~$18k → ~$1.8k/mo
Moved the workload from Lambda + FFmpeg to in-house Kubernetes workers.
~$500/mo
Identified resource-intensive queries and changed the surrounding systems.
~$400/mo
Used Karpenter with Spot + On-Demand capacity for resource-intensive workloads.
~$800 saved
Added expiry for ephemeral media and prevented storage from growing unchecked.
Systems I designed, owned or rebuilt — described at the architecture level rather than as a list of technologies.
185 models, 211 background workers and ~28 Sidekiq queues serving a regional social network. Four years of feature work, performance work, and the discipline of keeping a large monolith habitable.
Helm charts, per-environment values and automated image bumps describing every service in production — most changes deliberately small, so the tree stays reviewable.
NestJS and Socket.IO with Redis pub/sub for cross-instance fan-out and MongoDB for persistence. Three years of ownership — including adding a message broker and later removing it.
A live migration from AKS to EKS — Terraform for the new estate, one service at a time, DNS and CDN last, then a deliberate decommission. No maintenance window.
Compositing user photography onto templated poster and video designs at festival-day volumes. Moved from Lambda + FFmpeg to KEDA-scaled in-cluster workers driven by queue depth.
Background removal moved from per-call cloud API to an ONNX model on GPU nodes in-cluster, then a face-detector swap validated against 200 real production images before shipping.
Targeting users by district, state, party and circle, then dispatching push through FCM without touching the main API's request path.
CircleCI with timing-based test splitting, build capacity on our own cluster, plus the instrumentation and backup drills that make production legible.
An inverted index, BM25, Levenshtein automata, FSTs, BKD trees, a byte-level segment format and a breakable cluster — ~20,000 lines of TypeScript with a 43-chapter book.
Parses a Rails codebase with tree-sitter and generates Goravel Go code for models, CRUD controllers, Sidekiq workers, Pundit policies and RSpec scaffolds — automating the bulk of the structural work, with a strict mode that refuses partial output.
View source ↗A Ruby gem that tracks in-flight Sidekiq jobs and re-enqueues whatever a killed worker was holding, because Kubernetes evicts pods and Sidekiq does not remember what it lost.
View source ↗Alongside client and employer work, I design, build and run my own products end to end — client, API, data, infrastructure and launch.
A developer platform for the WhatsApp messaging APIs — connection management, wallet, API keys and production messaging from one workspace.
An AI hiring-operations workspace: resume intelligence, job-specific matching, technical assessments and one structured candidate pipeline.
Fixed-scope engagements for startups and product teams — from a focused review of an expensive or unreliable system to a complete product build.
Find the workloads, storage, database usage and capacity decisions driving an unexpectedly high AWS, GCP or Azure bill — then fix the ones that matter.
For startups whose cloud spend is growing faster than traffic or revenue.
You get · Written findings, a ranked savings plan with estimates, and hands-on fixes if you want them.
Trace a slow or unreliable workflow through services, queues, storage and infrastructure to identify the constraint that actually matters.
Before a major build, migration or scaling decision — or when dashboards show symptoms but not the root cause.
You get · Architecture notes, the root cause with evidence, and a prioritised remediation plan.
Review or set up deployment, autoscaling (KEDA, Karpenter), GitOps, observability and cloud migrations without a maintenance window.
For teams that grew quickly and want a reliable, understandable platform without a rewrite.
You get · A working, documented setup in your repositories — Terraform, Helm and runbooks your team can own.
Design and ship a production-ready product end to end: mobile or web client, API, data model, background jobs, infrastructure and launch.
For founders who need a working product — not a prototype that has to be rebuilt after the first customers arrive.
You get · A deployed product, source code you own, and a handover so your next engineer can take it forward.
Connect WhatsApp Business messaging to your product — notifications, conversational flows, queues and delivery tracking — built on the same stack as SoloSync.
For businesses that want reliable WhatsApp messaging without building the plumbing themselves.
You get · A production integration, or onboarding onto SoloSync's developer platform.
How an engagement works
01
Book a slot on Topmate and describe the problem. I tell you honestly whether I can help and what a first step would look like.
02
A written scope, timeline and fixed price before any work starts — no open-ended hourly billing surprises.
03
Regular written updates, work in your repositories, and documentation so your team owns the result.
Start with the problem
Send the context you already have. I reply within one working day and tell you whether a focused engagement makes sense before proposing any larger work.
Apr 2025 – Present
Circleapp Online Services (Praja)
Platform and infrastructure ownership alongside product work: the Kubernetes fleet, the media generation pipeline, and the release path everything ships through.
May 2022 – Mar 2025
Circleapp Online Services (Praja)
Backend feature work on the Rails monolith and the services around it, growing into the multi-cloud migration and the platform work that came with it.
Nov 2021 – Apr 2022
Circleapp Online Services (Praja)
Started on the Flutter client, then moved toward the API that fed it.
2021
Continual Engine
Applied-ML internship on image understanding for accessibility tooling.
The current stack is the result of solving the problems above, not the product itself.
B.Tech, Computer Science
Rajiv Gandhi University of Knowledge Technologies · 2022 · GPA 9.3 / 10
For backend, platform, infrastructure and focused technical consulting conversations.
Direct contact
Tell me what is expensive, slow, unreliable or difficult to reason about. A short description is enough to start.
Good fit