> GenAI & Backend Engineer @ Ascendion

I build production multi-agent LLM systems and the event-driven backends behind them.

I co-built Pensieve and architected the AAVA Code backend at Ascendion, and build open-source AI infrastructure in the open.

See my work Résumé

2K+: daily usersPensieve
3K+: daily usersAAVA Code · 5+ clients
8: open-source reposAI infrastructure

// production work @ Ascendion

Flagship systems I helped build

Co-built · production-hardened

Pensieve

AI Process-Orchestration Engine · Ascendion

A multi-agent LLM orchestration engine with human-in-the-loop approval gates, real-time streaming, and governed LLM routing across cloud providers.

2K+: daily users across domains
HITL: approval gates
Multi-cloud: governed LLM routing

Co-built · architected the backend

AAVA Code

AI Coding Plugin for VS Code · Ascendion

Re-architected a single-agent prototype into a multi-agent orchestration system (Main-Agent + sub-agent via crewAI flows) powering an AI coding plugin for VS Code.

3K+: daily users
5+: client environments
150+: skills · 40+ tools · ~60 commands

Co-built · production-ready

A GenAI-powered wireframe generator that converts product inputs (PRDs, sketches, prompts) into production-ready UI artifacts, built as a full vertical slice within Experience Studio over an SSE real-time architecture.

40%: fewer UX iteration cycles (5 rounds → 3)
60%: faster prototyping
500+: users daily

Co-built · production-ready

Prompt-to-React

Prompt-to-React Code Generation · Ascendion

A prompt-to-React code generation system that turns generated wireframes into production-ready modular components and routing logic.

50%: less frontend dev time (2 days → 1 per feature)
55%: less manual coding effort
2K+: developers
50+: teams

Co-built

Execution Engine

Prompt-Driven Execution Engine · Ascendion

A prompt-driven execution engine using LLM-based agent orchestration with RAG and ReAct pipelines that automates generation of structured product artifacts.

1.5h → 15m: workflow planning time
65% → 85%: first-pass acceptance
1.5K+: users

// open-source AI infrastructure

Things I build in the open

MindForge

Agentic-intelligence framework for Claude Code.

Command-driven multi-agent orchestration for Claude Code — 174 commands, 154 subagents, cost-aware model routing, and true wave parallelism. Ships as npx mindforge-cc.

Node.jsTypeScriptMCPsql.jsWebSocket

1,193 commitsDetails

Graph-Forge

AI-native distributed code-intelligence platform.

Models code as a Neo4j knowledge graph + Chroma embeddings over ~19 polyglot microservices, powering RAG over massive codebases with full observability.

GoPythongRPCNeo4jChroma

555 commitsDetails

Agent-Forge

Self-improving AI agent infrastructure.

A Karpathy-style propose/eval/score/commit-or-revert loop over a git-versioned agent spec, with an LLM-judge eval harness. Framework-agnostic.

PythonFastAPIpgvectorCeleryMCP

201 commitsDetails

Order Processing System

Distributed, event-driven gRPC microservices.

A polyglot Go + Python/FastAPI order-processing backend — Saga orchestration, CDC outbox, etcd leader election, and metric-based replica read routing.

GoPythongRPCPostgreSQLKafka

Code Intelligence & EnginesDetails

View all 8 projects

// competitive programming & impact

Recognition

Google Code Jam 2023

AIR 420 · 3,687 / 85,000+

Meta Hacker Cup 2022

4,048 / 70,000+

Flipkart GRiD 2022

Top tier · 1,325 / 40,000+

Institute Rank 1

GeeksforGeeks & InterviewBit

Mentored 250–300 students

Data Structures & Algorithms

// let's talk

Open to Backend, GenAI & Full-Stack roles

Building agent infrastructure or scaling an event-driven backend? I'd love to hear about it.

Email me LinkedIn GitHub

I build production multi-agent LLM systems and the event-driven backends behind them.

Pensieve

AAVA Code

Wireframe Generator

Prompt-to-React

Execution Engine