Pooya Golchian

I started shipping production code in 2012. The first half of the journey was frontend architecture across Angular, then Vue, then React, building admin panels and customer-facing apps for an e-commerce, a content company, and the InsurTech market in Iran. Different stacks, same job: turn a designer's intent into something that loads fast on the worst connection in the room.

The middle stretch hardened the discipline. At Haftcin I built high-traffic betting and live-casino platforms on Vue and Electron, with a parallel travel booking app on React Native. Real-time systems, payment integrations, cryptocurrency rails. Then Azkivam, where the work was Next.js with TypeScript, a 120-component Storybook library, and SSR optimization that took Lighthouse from 55 to 95 in a quarter.

Cashew Payments in Dubai was where the senior delivery muscle locked in. Payment gateway integrations with 99.99% uptime, fraud reduction work tied to the SEON SDK, and an Nx monorepo with seventy-plus reusable components that cut team delivery time by forty percent. Payment systems handling $10M+ per month across thousands of daily users. I ran accessibility and localization to WCAG 2.1 because regulated markets don't ship without it.

Three years ago the AI work began in earnest. Not as a side topic, as the centre of gravity. I architect production agent systems with LangGraph and the Vercel AI SDK, design Model Context Protocol servers that expose internal data to AI clients safely, and build RAG pipelines that survive document churn. I write eval suites before shipping. I worry about token economics the way I used to worry about CDN costs. I deploy private LLMs on customer infrastructure for industries where data residency is the only acceptable answer.

The work stays full-stack. Most engagements pair AI engineering with the rest of the stack the team is running: Next.js App Router, Node.js services, monorepos, durable workflows, the integration layer that makes a feature feel like one product instead of three bolted together. I write code my colleagues can own after I leave.

I run two companies in parallel with the consulting practice. Hisbi.ai builds AI products for B2B teams shipping into regulated markets, and Technova Solutions (codenovai.com) is the engineering studio behind several of the production deployments listed in my case studies. Founder seat at both, which is why I describe the role as AI Product Engineer rather than just engineer. The job is to ship the product, not just the code path.

Eight companies. Industries from fintech to insurtech to luxury retail to live gambling to AI-native B2B SaaS. The thread is the same line of work: senior engineering, shipped, in production, under deadline.