I like building the parts of software you don't see: gateways, rate limiters, booking backends and tools that keep ML experiments reproducible. Most of my work starts with "how would this hold up under real load?" and ends as something I can test and ship.
type Rameshwari struct {
Building []string
Learning []string
OpenTo []string
}
var me = Rameshwari{
Building: []string{"backend services", "API gateways"},
Learning: []string{"distributed systems", "system design"},
OpenTo: []string{"internships", "hackathon teams", "OSS collabs"},
}Languages
Backend & infra
Frontend
Databases & tools
|
An API gateway for microservices. Handles JWT auth, chained middleware, Redis-backed token-bucket rate limiting, dynamic reverse-proxy routing and central logging. |
A light, file-first toolkit for reproducible ML. Tracks datasets, params, preprocessing steps, metrics and artifacts without heavy infra. |
|
Movies, theatres, showtimes and bookings, with JWT auth, role-based access, MongoDB indexes and fast seat-availability lookups. |
Experiments, coursework and open-source contributions live on my profile. |
Cards are rebuilt daily by a GitHub Actions workflow in this repo, from public data only.
Building systems, solving problems, and learning in public.
