anubhav jain / portfolio

I like owning problems end to end.

Full stack software engineer, 8 years

Frontend, backend, infrastructure — whatever the problem actually needs. I've done that at enterprise scale, at startup speed, and across client work in healthcare and fintech. Lately I've been applying the same approach to AI.

why I build this way

Philosophy

I don't like stopping at the abstraction. If I'm using something — a framework, a system, a model — I want to understand it well enough that I could have built it myself. That's not a purity test, it's practical: you can't debug, extend, or trust something you don't actually understand.

That instinct is the thread through everything I've worked on. At an enterprise scale, it means understanding a system deeply enough to know exactly where a change is safe and where it isn't. At a startup, it means being comfortable owning a problem with no playbook, because someone has to figure out what "done" even looks like. Across client work, it means going deep enough into someone else's domain — healthcare compliance, fintech regulation — to build something that actually holds up.

More recently I've turned that same instinct toward AI. I use tools like Claude Code to move fast, but I treat them as leverage, not a replacement for understanding. I still work through the mechanics myself — training runs, architecture decisions, what actually happens inside the model — because that's the only way I trust what I've built.

I'm drawn to problems where the easy version isn't good enough. Where "mostly working" doesn't count, and the interesting part is making the whole thing actually hold together.

where I've done this

Experience

2023 — present

Senior Engineer II, PowerSchool

Production reliability for a large multi-tenant SaaS platform. Incident recovery, root cause analysis, and building guardrails so failures don't repeat.

2021 — 2023

Product Engineer, Shuru Technologies

One of the first engineers at a startup that pivoted from youth training into hiring. Built across the whole stack as the product changed underneath us.

2019 — 2021

Software Engineer, Betacraft Technologies

Client engagements across healthcare and fintech. Led a compliance and continuing-education platform for clinicians, built on a complex rules engine.

2018 — 2019

Systems Engineer, Infosys

SAP Basis operations. Early exposure to enterprise systems and production discipline.

what I've built on the side

Projects

Vision-language model, from the ground up

write-up in progress

A model that can look at an image and describe it in natural language. Built and trained end to end — not to invent something new, but to understand exactly how the pieces fit together, using Claude Code as a pair-engineer along the way.

vision-language SigLIP2 Qwen2.5 Claude Code

Image and caption, generated together

write-up in progress

A system that generates a stylized image and a matching caption from a single input, rather than generating one and describing it after the fact. Combines an image-generation model with a captioning model trained to stay coherent with it.

diffusion LoRA CLIP multimodal

Compliance platform for clinicians

Betacraft, 2019–2021

A platform helping clinicians track and meet continuing-education and compliance requirements, built on a rules engine that encoded a demanding, ever-changing set of regulations. Integrated with partner systems to keep compliance data accurate across sources.

Ruby on Rails rules engine healthcare