I'm Binaya Tripathi— architecting agentic AI systems, RAG pipelines and production LLM apps with Claude, GPT-5, LangGraph and MCP. Next.js on the front, FastAPI on the back, shipped on AWS Bedrock, Azure OpenAI & GCP Vertex AI.
Senior Full-Stack AI Engineer @ Builders Academy — mentoring 50+ devs on Claude, Cursor & MCP.
12+ years moving between research-grade ML, production web infra, and product thinking — turning frontier LLMs into shippable products people actually use.
I architect end-to-end LLM-powered web apps — combining React / Next.js / TypeScript fronts with Python (FastAPI) and Node.js backends. I've shipped agentic AI tools, RAG pipelines with pgvector & Weaviate, and production LLM services on AWS Bedrock, Azure OpenAI and GCP Vertex AI. I care about evals, observability, and cost — not just demos.
LLM products, AI storytelling SaaS, and commerce at scale. Each shaped by real constraints and measurable outcomes.
An AI-generated content platform that combines multi-modal LLM generation with on-chain authenticity verification. Creators mint articles, audio, and visuals, each signed and provenance-tracked via Web3 primitives.
A magical story generation platform for families, powered by streaming LLMs, safety guardrails, and a credits-based billing model. 100+ stories generated, 30+ happy kids, and scaling.
A responsive e-commerce platform scaled to 2M+ monthly sessions and 200K+ SKUs. Cut checkout latency from 3s to 1s via Redis caching, NGINX load balancing, and a lean React + Node.js stack.
I'm wary of AI theater. Here are the four rules that have held up across 12 years and five engineering roles.
Every LLM feature ships with an eval harness — offline + online. If we can't measure it, we don't claim it.
Model choice, prompt caching, context discipline. I've cut real LLM bills by 45% without losing quality.
LangGraph state machines, MCP tools, and guardrails. Autonomous where it wins, human-gated where it matters.
AI features need auth, billing, observability, retries, and migrations. I build all of it — front to back.
From classical ML at scale to frontier agentic AI — condensed timeline of systems shipped and measurable impact.
Production-tested across agentic pipelines, SaaS platforms, and e-commerce at 2M+ sessions — not a sandbox list.
Open to Senior / Staff Full-Stack AI Engineer roles, GenAI product teams, and consulting engagements on LLM apps, agents, and RAG infra. Ping me — I read every message.