Software Engineer · Backend · Applied AI / LLM systems

Portfolio · LinkedIn · Email · llms.txt

I'm a software engineer based in India, working remote. Most of my time goes to backend services and the front ends that sit on them — APIs, data models, background work, and lately the server-side plumbing around LLM features.

The part I enjoy most is efficiency. Making something cost less to run or return faster, and being able to point at a number that says so. I like measuring before changing anything, because the bottleneck is usually somewhere other than where I'd have guessed. That interest is pulling me toward inference and serving performance — latency, throughput, batching, cost — which is where I'm reading and building at the moment.

• Large React and TypeScript front ends — shared state across many screens, multi-language, long-lived codebases where the conventions matter more than any single feature
• Backend services — Python and Node, REST APIs, relational data modelling, migrations, background jobs, containers and deployment
• LLM features on the server side — tool and function calling, structured output, keeping model output on the untrusted side of a boundary, and watching what it costs per call
• UIs inside constrained host platforms — sandboxed runtimes where you don't get to just call fetch, and everything goes through a bridge with its own rules
• Async execution — execute, poll, cancel, retry, and making duplicate requests harmless
• Scheduled pipelines — pull from a source, filter it, publish a versioned artifact something else reads at runtime
• Enterprise and regulated contexts — access boundaries, approval steps, audit trails, and being careful about what data is allowed to go where
• Cost and performance work — profiling, benchmarking, and picking the cheaper option only once there's a measurement behind it

Working through the ML and inference side — PyTorch, profiling, batching, and what actually moves latency and cost when you serve a model. Engineering is the job; the stack follows the problem. This is the direction I'm growing in.

Languages

Backend and data

Infrastructure

AI engineering

Frontend

_{Older repositories here are practice work from 2022–23 and don't represent current output.}

For roles, dates and employment history, the résumé covers it. The same facts in machine-readable form live at ashishkrjha.dev/llms.txt.

name: Ashish Kr Jha
title: Software Engineer
focus: [backend engineering, applied AI / LLM systems, full-stack]
open_to: [backend, applied AI / LLM systems, AI platform, TypeScript/Node backend]
interests: [cost and performance optimisation, measurement and benchmarking,
            inference and serving efficiency]
location: India (remote)
languages: [Python, TypeScript, JavaScript, SQL]
backend_and_data: [FastAPI, Node.js, REST APIs, PostgreSQL, SQLAlchemy,
                   Alembic, Redis]
infrastructure: [Docker, Google Cloud, Cloud Run, Cloud Scheduler,
                 Cloud Storage, Git]
ai_engineering: [LLM API integration, tool/function calling, structured outputs,
                 agent workflows, prompt-injection boundaries,
                 token and cost budgeting]
frontend: [React, Next.js, Redux Toolkit, Vite, Tailwind CSS]
portfolio: https://www.ashishkrjha.dev
resume: https://www.ashishkrjha.dev/Ashish_Kr_Jha_Resume.pdf
linkedin: https://www.linkedin.com/in/ashish-kumar-jha-59303520b
github: https://github.com/AshishJha14411
email: ashishjha14411@gmail.com

ashishjha14411@gmail.com · ashishkrjha.dev