YURIY CHUKAEV · ychukaev.dev

Yuriy Chukaev

Senior Full-Stack / Backend Engineer

I build third-party integrations, business-process automation and production LLM pipelines for founders and product teams. 10+ years shipping commercial software, hands-on from schema to deploy.

PHP 8PythonTypeScript / React Node.jsLLM / AI pipelinesCRM & payment integrations
Remote · Santos, Brazil (UTC-3, no DST)
5–6h daily overlap with US East · async-first
Available for contract / PJ work
invoice in USD · worldwide · no visa sponsorship needed
Track record

Proof, in numbers

10+ yrs
commercial software engineering
70,000+
calls analyzed by an AI pipeline I built
43,000+
requests routed in production
40,000+
parcels/day at peak on a platform I built
300+
companies integrated over a product's lifetime
14,000+
SKUs on an e-commerce platform I built
I own delivery end to end — architecture, code, third-party integrations, deployment and long-term evolution. You talk to the engineer who writes the code.
Case 01 · On-demand operations + AI intake

From paper notebooks to a live operations app

Problem

An on-demand florist-retail business ran every order through paper notebooks and chats. Managers matched florists and couriers by hand, order by order — the bottleneck any on-demand service hits as it grows.

Approach

A role-based PWA (installs like a native app) with a separate cabinet per role — florists, couriers, managers, accounting — covering the whole order lifecycle: intake → "take the job" → assembly → photo confirmation → automatic payment request. On top, an AI consultant answers customers across three channels, checks live stock and price, upsells, and opens the order automatically; the owner edits how it talks right in the app, every change versioned.

Stack: React + Vite + TypeScript · FastAPI · async SQLAlchemy · PostgreSQL · CRM API (amoCRM v4) · LLM consultant · PWA
Impact: the full order lifecycle in one system, instant 24/7 first response, nothing lost in chats — with the business, not the vendor, in control of the assistant.
Read the case — architecture & decisions →
Order queue — role-based operations app
Owner-editable AI consultant prompts
Case 02 · E-commerce & integrations at scale

A pharmacy chain, fully online

Problem

A regional pharmacy chain (13 stores across two countries, 6 legal entities) needed to sell online — with live stock per store, regulated products, local pricing and lawful fiscal receipts.

Approach

I migrated the chain off a boxed CMS onto a custom PHP 8.3 engine with deep two-way integration to two pharmacy ERPs, payment routing across legal entities, fiscalization, delivery integration, messenger bots, and a multi-region plus second-country launch.

Stack: PHP 8.3 · MySQL · REST & webhook ERP integrations · payment gateways · fiscalization · delivery API
Impact: 14,000+ products across 6 regional storefronts, live per-store stock and pricing, payments and delivery wired end to end across six entities and two countries.
Read the case — architecture & decisions →
Pharmacy e-commerce catalog, 14,000+ products
Case 03 · Production AI & automation at scale

AI that listens, scores and fills the CRM

70,000+
calls analyzed in production

A production AI product (my own) listens to calls and chats, fills the CRM automatically, scores quality and flags risks. In its first 2.5 months it analyzed 70,000+ calls (1,200+ hours of audio) and ran 31,000+ automated checks, isolated per client.

Stack: Python · speech-to-text · LLM scoring (Anthropic / Gemini) · CRM autofill
43,000+
requests routed in production

A distribution engine that routes each inbound request to the right available person in seconds, by configurable rules — load, skills, schedule, priority. In production since 2022, with a client I have supported since 2018.

Stack: Python · rules engine · CRM & telephony integrations · webhooks
Read the case — architecture & decisions →
These systems run inside clients' CRMs, so I show them anonymized here and live on a screen-share call. Other work in my track record: an amoCRM widget platform (23 sub-widgets on a custom PHP backend) and a booking PWA with end-to-end marketing attribution for a medical clinic.
Stack · how I work · contact

What I bring, and how we'd work

Backend
PHP 8 (Laravel, Symfony), Python (FastAPI, Flask), Node.js
Frontend
JavaScript, TypeScript, React, PWA (service workers, web-push)
Integrations & APIs
REST APIs, webhooks, CRM Widget SDK & API (Kommo / amoCRM), payment gateways, ERP & delivery APIs, telephony (SIP / VoIP), IMAP / SMTP
AI & LLM
Production LLM pipelines, RAG, tool / function calling, structured outputs, speech-to-text; OpenAI & Anthropic APIs
Data & Infra
PostgreSQL, MySQL, Redis, Docker, Nginx, Linux, CI/CD

You talk to the engineer who writes the code — no juniors, no hand-offs. I take a project from an ambiguous spec to production and keep it running and evolving. Weekly demos, async-first (written updates, PRs), comfortable on calls.

Availability & engagement

Available now — remote contract (Brazil PJ / independent contractor), invoice in USD via Wise / Payoneer. Worldwide, US-hours friendly. No visa sponsorship or EOR needed.
Languages: English — professional working (CEFR B1+) · Portuguese — basic · Russian — native.

© 2026 Yuriy Chukaev · ychukaev.dev Senior Full-Stack / Backend Engineer · Remote · Santos, Brazil (UTC-3)