I'm Jaydip, an engineer based in India shipping AI agents, LLM applications, and automation systems for startups and growing teams. Seven years of production full-stack experience — the kind of code that has to hold up, not just demo well.
The gap between a shiny AI prototype and a production system is where most projects die. I live in that gap.
My work sits at the intersection of LLMs, autonomous agents, and traditional engineering — grounded in seven years of shipping full-stack products that still run long after the launch post.
I care about the unglamorous parts: evals, error handling, latency, unit economics, and the question what happens when this actually gets used?
Autonomous agents, RAG pipelines, tool-use systems, and chat interfaces built on OpenAI, Anthropic, and open-source models — with proper evals and guardrails.
Workflows that replace manual ops — scraping, enrichment, routing, notifications — wired into your existing stack with observability built in.
End-to-end products with auth, billing, and admin panels. React, Next.js, Node, Laravel — whatever the problem actually needs.
REST & GraphQL APIs, third-party integrations, webhook infrastructure, and AI-ready backends designed for scale.
Deployment, CI/CD, monitoring, cost optimization. AWS, GCP, DigitalOcean, Vercel — whatever keeps it running smoothly.
Flutter and React Native apps that share logic with web, with native polish where it matters.
A short call to unpack the business goal behind the request. I'd rather spend time here than fix misalignment later.
Clear scope, milestones, and pricing — no vague line items. You'll know exactly what you're getting.
Weekly progress, staging environments, async updates. You see what's happening as it happens.
Monitoring, handover, and ongoing support. I'd rather you succeed than re-hire me for a cleanup.