Bohdan

Python-програміст

Розглядає посади:
Python-програміст, Python Backend Developer at UnderTalk | FastAPI · Async · AI/LLM Integ
Вид зайнятості:
повна, неповна
Вік:
19 років
Місто проживання:
Київ
Готовий працювати:
Дистанційно

Контактна інформація

Шукач вказав: ТелефонЕл. поштуLinkedInМесенджер

Прізвище, контакти та світлина доступні тільки для зареєстрованих роботодавців. Щоб отримати доступ до особистих даних кандидатів, увійдіть як роботодавець або зареєструйтеся.

Досвід роботи

Middle Python Developer | AI / LLM

з 04.2026 по нині (6 місяців)
Undertalk, кол-центр, Дистанційно (Телекомунікації, зв'язок)

Building a multi-module call-center CRM from scratch — independent modules over a shared operator/client data layer, in a microservice layout with Celery / RabbitMQ / Redis workers.

Delivered end-to-end in the last two months: operator workspace, discipline control, telephony analytics, shift scheduling and recruiting. I own the full cycle on each — requirements with the client, spec, database schema, implementation, tests, production deployment and incidents. Vue.js frontend where a module needs it.

- Shipped a production MCP server — 38 tools that let Claude configure payroll rules from chat: schema introspection, validation, salary simulation on real data, gated write path. MCP runs as a second transport over the same executors as the API.

- Hardened it for production: the write tool refuses to persist unless validation and a money-impact simulation both passed — any edit resets the gate, so an agent can't save a config no human priced. OAuth 2.1 (Auth0), connector forwarding the caller's own token.

- Built the in-CRM AI copilot on the same tools — an Anthropic tool-use loop that self-corrects on tool errors.

- Built operator analytics and client analytics as separate subsystems, computed per connected CRM and aggregated across all of them. Client complexity is a weighted coefficient over three normalized metrics, recomputed nightly.

- Integrated Binotel telephony, external CRMs and order sources, and Viber chat (text, media, MinIO) — via webhooks, polling APIs and queues, with idempotent syncs and an identity-mapping layer that resolves the same operator or client across systems that identify them differently.

- Designed a configurable discipline rules engine (three parameterized rule types — new thresholds ship as configuration, not code) and the QA subsystem behind it: pause accounting, a violation state machine and an audit trail.

Stack: Python · FastAPI · PostgreSQL · SQLAlchemy async · Celery · RabbitMQ · Redis · Claude API · MCP · Docker · Vue.js

Python developer

з 01.2025 по 03.2026 (1 рік 3 місяці)
SECL Group, Дистанційно (IT)

Backend developer (Python) on a production web platform, working inside a cross-functional team under a strict PR-review process.



Worked across several backend modules — authentication, client records, notifications and reporting — implementing endpoints, data access and background logic, and taking each one through review to release.



- Shipped Alembic migrations against a live production database with zero downtime.



- Profiled and rewrote the slowest queries on the highest-traffic endpoints.



- Replaced browser-side polling of our own API with a WebSocket layer for real-time push notifications, and added Redis caching on hot endpoints — cut redundant requests and reduced server load.



- Integrated third-party services over REST APIs, including Google Calendar (OAuth 2.0, event synchronisation).



- Tracked down and fixed recurring production incidents in JWT auth and async session handling — session lifecycle, transaction boundaries and data consistency under concurrent load.



- Every change reviewed and tracked in Jira; ran Docker-based production deployments on Ubuntu.



Stack: Python · FastAPI · PostgreSQL · SQLAlchemy async · Alembic · Redis · WebSockets · Pydantic V2 · Docker · Linux

Освіта

Online School, ProgAcademy

IT, Київ
Вища, з 2023 по 2023 (менш ніж 1 рік)

Python Backend Developer

Додаткова освіта та сертифікати

Немає додаткової освіти та сертифікатів.

Знання і навички

  • Здатність до навчання
  • Python
  • Git
  • SQL
  • Знання принципів ООП
  • PostgreSQL
  • Docker
  • SQLite
  • REST
  • FastAPI
  • GitHub
  • Alembic
  • Asyncio
  • SQLAlchemy
  • Unit Of Work
  • Pydantic
  • Clean Architecture
  • REST API
  • Django
  • CSS
  • HTML
  • MySQL
  • Комунікабельність
  • Redis
  • JSON Web Token
  • Docker Compose
  • Asynchronous programming
  • Pandas
  • Celery
  • WebSocket
  • JavaScript
  • Node.js
  • RabbitMQ
  • Postman
  • Google API

Знання мов

  • Англійська — середній
  • Німецька — початковий
  • Українська — вільно
  • Польська — вільно

Додаткова інформація

Python backend developer with 2 years of commercial experience building production
async systems on FastAPI — and shipping LLM features that run in production, not in demos.

Right now I'm building a multi-module call-center CRM from scratch at UnderTalk:
microservices over a shared operator/client data layer, Celery / RabbitMQ / Redis workers,
Docker and Docker Compose across dev and prod. In the last two months I delivered five
modules end-to-end — operator workspace, discipline control, telephony analytics, shift
scheduling and recruiting — each from requirements with the client through schema design,
implementation, tests and production deployment. Plus the analytics subsystem behind the
operator and client dashboards.

The part I'm proudest of: an MCP (Model Context Protocol) server with 38 tools that lets
Claude configure live payroll rules from chat. OAuth 2.1 with Auth0, a write path that
refuses to save until validation and a money-impact simulation both pass, concurrency-safe
per-session state. The same tools sit behind an in-CRM AI copilot — an Anthropic tool-use
loop that self-corrects on tool errors.

Integrations are a large part of what I do: telephony (Binotel), an external CRM and order
source, Viber messaging — over webhooks, polling APIs and message queues, with idempotent
syncs so a retried event never produces duplicates.

Side projects, all with real test coverage and CI: Trend Radar (Playwright scraping +
5 LLM providers with deterministic fallback, 231 tests), a full e-commerce platform live
on AWS EC2, a RAG pipeline over PDFs, and a Telegram job bot.

Code: github.com/bogdan0089

Open to Python Backend / AI Engineer roles — remote.

Ukrainian (native) · Polish (C2) · English (B2)

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