AI ENGINEER / BENGALURU, INDIA

Intelligence,
engineered for
production.

I’m Himanshu. I build AI agents, intelligent applications, and the infrastructure that takes them from idea to production.

Currently building at OnFinance AI
IIT Kharagpur · Economics → Engineering
system.architecturev1.0
FROM REQUEST TO RESPONSE
02 / ORCHESTRATION

LangGraph connects reasoning, tools, and context into configurable agent workflows.

Select a node to explore

An illustrative workflow, inspired by my engineering work.

100M+LLM tokens processed
per month
20+Enterprise client
deployments
$260K+Infrastructure credits
secured
01 / SELECTED WORK

Built. Shipped. Open.

Explore GitHub

A few things I’ve put into the world.

AGENT WORKFLOWdurable · streaming
SANDBOX VMfsshellgitdev serversnapshot · resume
THE AGENT IS NOT THE SANDBOX.
ARCHITECTURE ILLUSTRATION
OPEN SOURCE / CLOUD AGENTS 05

Open Agents

Coding agents that live in the cloud. A durable workflow drives an isolated sandbox VM through tools, so the agent and the machine it works on stay separate.

FORK Built on vercel-labs/open-agents (MIT). My fork adds a hardened MongoDB connector to the Python agent.

TypeScriptNext.jsSandbox VMPython
annual-report.pdfp. 04
§1 Overview
§2 Financial statements
§2.1 Revenue table
PAGES SECTIONS BOXES
DOCUMENT TREE ILLUSTRATION
DOCUMENT INTELLIGENCE 06

Hierarchical Document Parsing

A document as a tree, not a blob. Vision calls infer section boundaries and describe every node, so an agent can walk the structure instead of re-reading the page.

INTERNAL Built at OnFinance AI. No public repository.

Claude Haiku 4.5VisionAgentic traversal

Showing all 6 projects.

02 / EXPERIENCE

Where the work gets real.

Download profile
JUN 2025 — PRESENT

AI Engineer CURRENT

OnFinance AI · Bengaluru

Building AI agents for risk, audit, and compliance in financial services.

  • Architected Agent Studio: a LangGraph workflow engine with a connected file system, dynamic tool registry, and skill-based prompt routing, orchestrating AI pipelines across multiple product verticals.
  • Engineered LLM, RAG, and document intelligence pipelines processing 100M+ tokens per month, using LiteLLM, AWS Bedrock, OCR, FusionQuery search, and re-ranking.
  • Built clause-level RAG pipelines and agentic workflows over SEBI, RBI, and IRDAI regulatory data and compliance circulars.
  • Owned AWS Kubernetes infrastructure and client delivery across 20+ enterprise accounts, including NSE, BSE, Axis Finance, BharatPe, and PayU Finance, spanning SaaS and on-premise deployments.
  • Operated MongoDB, Redis, Qdrant, RabbitMQ, and Trino, with delivery through GitHub Actions and Argo CD.
  • Secured $260K+ in infrastructure credits through AWS and the Cloudflare Startup Program.
  • Contributed to a $4.2M Pre-Series A from Peak XV Partners through technical demos and executive product presentations.
LangGraphAWS BedrockKubernetesRAGArgo CD
MAY — JUN 2025

LLM Trainer

Outlier · Remote

RLHF preference ranking and pairwise comparison of model responses across coding and reasoning tasks, with evidence-based justifications for every rating.

  • Authored structured feedback and failure-mode annotations used to shape reward-model signals for downstream reinforcement learning.
  • Reviewed code generation for correctness, efficiency, and adherence to task specifications.
RLHFPreference rankingModel evaluation
OCT — DEC 2024

LLM Trainer

Soul AI

Evaluated and benchmarked multi-model LLM outputs across STEM and non-STEM domains for factual accuracy, reasoning, and response quality.

  • Audited agent tool-calling behaviour, validating function-call schemas, parameter correctness, and API integration reliability in code-execution traces.
  • Engineered prompts with zero-shot, few-shot, and chain-of-thought techniques to improve reasoning consistency.
Model evaluationTool callingPrompt engineering
MAY — JUL 2024

AI Intern

Schneider Electric · Bengaluru

Built a GenAI knowledge bot for developers, using retrieval-augmented generation over internal documentation and codebases to return source-grounded answers and code references.

  • Prototyped GenAI across knowledge management, automated testing, and code assistance, evaluating LLM integration patterns and embedding-based retrieval.
  • Designed semantic indexing and vector search over internal documentation to improve discoverability of engineering knowledge org-wide.
RAGGenerative AIVector searchDeveloper tooling
SEP — DEC 2023

AI Research Intern

Indian Institute of Technology, Kharagpur

Research internship at IIT Kharagpur, alongside my M.Sc. in Economics.

AI researchIIT Kharagpur
03 / THE ENGINEER BEHIND THE CODE

An economist’s lens.
An engineer’s instinct.

I studied Economics at IIT Kharagpur. Today, I work at the intersection of business and AI: understanding the problem, designing the system, and getting it into production.

I enjoy the whole journey, from raw data and model behaviour to agent orchestration and the infrastructure underneath. The goal stays the same: build something useful that works in the real world.

A little outside the terminal.

Photography and filmmaking. Former Head of Photography and Advisor at IIT Kharagpur’s Technology Filmmaking and Photography Society.

Institute Order of Merit SOCIAL & CULTURAL

Awarded by IIT Kharagpur’s Technology Students’ Gymkhana for distinguished contribution to social and cultural life on campus — the Institute-level tier, above Honourable Mention and Special Mention.

IIT Kharagpur
M.Sc. Economics · 2020–2025
7.9 / 10.0 CGPA
AI4ICPS Certificate Programme
MY WORKING STACK
01

Intelligence

LLMs, agents & retrieval

PythonLangGraphLangChainLlamaIndexLiteLLMAWS BedrockGroqPrompt engineering
02

Machine learning

Models, training & evaluation

PyTorchTensorFlowKerasScikit-learnXGBoostLightGBMTransformersspaCy
03

Infrastructure

From deployment to operations

AWSKubernetesDockerLinuxGitHub ActionsArgo CDCloudflareBifrost
04

Data systems

Context, storage & communication

SQLMongoDBQdrantPineconeChromaDBRedisRabbitMQTrinoMySQL
05

Applications

Interfaces & analysis

FastAPIPydanticTypeScriptSwiftStreamlitDashPandasPower BI
04 / WHAT’S NEXT?

Have an interesting
problem? Let’s build.

I’m open to conversations about AI engineering, intelligent products, and the systems behind them.

PROJECT NOTES

View source
Selected work 01 ↵Experience 02 ↵About & stack 03 ↵Get in touch 04 ↵GitHub View profile PDF