Raj Vadeghar

Full-stack engineer · AI systems · Since 2022
Raj Vadeghar portrait
Currently

Chat4Team

Building a customer support platform for a European manufacturer. Hybrid RAG, streaming replies, multi-tenant infrastructure. 100K+ messages in production.

Open for

New work →

AI platforms, Chrome extensions, full-stack web apps, and cloud infrastructure. One or two engagements at a time.

Start a project
60K
Chrome ext. users
104K
AI messages live
80%
AI acceptance
98%
Embedding cost ↓
26
MV3 migrations
React / Next.jsTypeScriptNode · Express.NET / C#PostgreSQL · pgvectorClaude · OpenAIVoyage embeddingsBM25 + RRF hybrid searchVercel AI SDKChrome MV3AstroAWS · Azure · VPSDocker · Podman · CaddyReact / Next.jsTypeScriptNode · Express.NET / C#PostgreSQL · pgvectorClaude · OpenAIVoyage embeddingsBM25 + RRF hybrid searchVercel AI SDKChrome MV3AstroAWS · Azure · VPSDocker · Podman · Caddy
Services

Four disciplines.
One engineer.

01

AI platforms

Production RAG systems, streaming replies, and multi-tenant infrastructure. Chat4Team processes 100K+ messages with 80% reply acceptance.

  • Hybrid retrieval (pgvector + BM25 + RRF)
  • Vercel AI SDK · Claude / OpenAI orchestration
  • Human-in-the-loop operator tools
02

Web applications

Full-stack TypeScript in React, Next.js, and Astro. Type-safe end to end, with real auth, real payments, and clean migrations.

  • Type-safe full-stack (Zod → DB → UI)
  • SSR / ISR / edge-ready
  • Analytics and SEO configured by default
03

Chrome extensions

Manifest V3 at scale. 55,000+ users, 26 storage migrations, zero data loss.

  • Service-worker architecture
  • Storage, sync, and offscreen audio
  • Store listings and rollout strategy
04

Cloud & infra

.NET and Azure Functions at TCS-scale. Self-managed Podman and Caddy on bare VPS. Zero-downtime deploys with health checks and rollback paths.

  • Zero-downtime deployments
  • Azure, AWS, and self-managed VPS
  • PowerShell and Bash automation
Operating principles

How I work.

01 / Shape

Problem before stack.

Every engagement starts with the problem, not the framework. Time invested upfront on scope and constraints prevents months of rework later.

02 / Ship small

Incremental delivery.

Small, reversible pull requests. CI/CD, health checks, and migrations built in from day one — never retrofitted at the end.

03 / Own it

Architect through on-call.

I build, deploy, and support the systems I design. Handoffs are documented, predictable, and engineered to be handed off.

04 / Write it

Written decisions.

Architecture decisions, trade-offs, and postmortems are documented. The next engineer should be able to read the system without talking to me first.

Currently shipping

Current engagements and writing.
Active engagement

Chat4Team

Customer support platform for a European manufacturer. Hybrid RAG over documents, scraped pages, and resolved support tickets. Streaming replies, human-in-the-loop operator tools, zero-downtime deployments on self-managed infrastructure.

100K+
Messages handled
80%
AI reply acceptance
~98%
Embedding cost cut

Two years in production. The architecture here — hybrid retrieval with a reranker, streaming responses, and operator tools — has become the template for every AI system I build.

TypeScriptpgvectorClaudeVercel AI SDKSocket.IOCaddy
Writing

Field notes on production systems.

Long-form writing at r44j.dev on the systems I've built — RAG pipelines, Chrome extension migrations, zero-downtime deployments. Documentation of what worked, what failed, and the decisions behind each call.

AstroSanity CMSMDX
Open for new engagements

Have a project
in mind?

One or two engagements at a time. AI platforms, Chrome extensions, full-stack web applications, and cloud infrastructure. Scoped on the first call.