Semen Hoinets
Lisbon, Portugal
Semen Hoinets
SENIOR FULL-STACK ENGINEER
Category : Web development
Senior Full-Stack Engineer with 5+ years building scalable SaaS products
using Python (FastAPI/Django), React/Next.js, and PostgreSQL. Experienced
in integrating AI/LLM features, including RAG pipelines, OpenAI API, and
vector databases. Track record of shipping MVPs from scratch, scaling
platforms from hundreds to 20,000+ users, and improving
conversion/performance by measurable margins. Available 30–40 hrs/week
for long-term partnerships.
using Python (FastAPI/Django), React/Next.js, and PostgreSQL. Experienced
in integrating AI/LLM features, including RAG pipelines, OpenAI API, and
vector databases. Track record of shipping MVPs from scratch, scaling
platforms from hundreds to 20,000+ users, and improving
conversion/performance by measurable margins. Available 30–40 hrs/week
for long-term partnerships.
Working hours
- Monday:10h00 To 18h00
- Tuesday:10h00 To 18h00
- Wednesday:10h00 To 18h00
- Thursday:10h00 To 18h00
- Friday:10h00 To 18h00
- Saturday:Not available
- Sunday:Not available
Led backend architecture and REST API design using Python, Django,
and FastAPI, reducing API response time by 42% and achieving 99.9%
platform uptime across AWS infrastructure.
Modernized the frontend with React and Next.js, optimized PostgreSQL
indexing, and implemented Redis caching, scaling the product from
2,000 to 18,000+ active users.
Improved onboarding flow and subscription billing, increasing conversion
rates by 27% and dashboard engagement by 31%.
Integrated OpenAI API and built a RAG pipeline with pgvector and
LangChain to power an in-app AI assistant, reducing support ticket
volume by ~30%.
Containerized the full application stack with Docker and Kubernetes on
AWS EKS; implemented blue-green deployments via GitHub Actions
CI/CD, reducing deployment downtime to near zero.
Wrote 300+ unit and integration tests using pytest and React Testing
Library, reaching 85% coverage and cutting regression bugs by 40%.
Mentored 2 junior engineers, led sprint planning, and collaborated with
product and design to define technical roadmap.
and FastAPI, reducing API response time by 42% and achieving 99.9%
platform uptime across AWS infrastructure.
Modernized the frontend with React and Next.js, optimized PostgreSQL
indexing, and implemented Redis caching, scaling the product from
2,000 to 18,000+ active users.
Improved onboarding flow and subscription billing, increasing conversion
rates by 27% and dashboard engagement by 31%.
Integrated OpenAI API and built a RAG pipeline with pgvector and
LangChain to power an in-app AI assistant, reducing support ticket
volume by ~30%.
Containerized the full application stack with Docker and Kubernetes on
AWS EKS; implemented blue-green deployments via GitHub Actions
CI/CD, reducing deployment downtime to near zero.
Wrote 300+ unit and integration tests using pytest and React Testing
Library, reaching 85% coverage and cutting regression bugs by 40%.
Mentored 2 junior engineers, led sprint planning, and collaborated with
product and design to define technical roadmap.
Integrated Stripe API for payments and optimized backend performance
using Django and Redis, reducing checkout abandonment by 18%.
Redesigned the React-based admin dashboard and improved the page
performance, increasing Lighthouse score from 63 to 91.
Automated inventory synchronization via Celery async workers, saving
15+ hours of manual work per week.
Built an AI-powered product recommendation engine using OpenAI
embeddings and cosine similarity search, increasing average order value
by 12%.
Migrated CI/CD from manual deploys to GitLab CI pipelines with
Dockerized environments, cutting the release cycle from 2 weeks to 3 days.
Introduced a pytest test suite with 70%+ coverage on critical payment and
inventory modules, eliminating a recurring class of checkout bugs.
using Django and Redis, reducing checkout abandonment by 18%.
Redesigned the React-based admin dashboard and improved the page
performance, increasing Lighthouse score from 63 to 91.
Automated inventory synchronization via Celery async workers, saving
15+ hours of manual work per week.
Built an AI-powered product recommendation engine using OpenAI
embeddings and cosine similarity search, increasing average order value
by 12%.
Migrated CI/CD from manual deploys to GitLab CI pipelines with
Dockerized environments, cutting the release cycle from 2 weeks to 3 days.
Introduced a pytest test suite with 70%+ coverage on critical payment and
inventory modules, eliminating a recurring class of checkout bugs.
Built and deployed a production-ready MVP within 10 weeks using
FastAPI, PostgreSQL, and Docker, securing seed funding post-launch.
Designed a scalable cloud architecture on AWS (EC2, RDS, S3), reducing
operational costs by 28% and ensuring zero critical incidents in the first 6
months.
Integrated OpenAI API for automated content generation feature,
enabling the product to go to market faster without additional editorial
headcount.
Set up Docker Compose for local dev environments and GitHub Actions
pipeline for automated testing and deployment to AWS, reducing dev
onboarding from days to hours.
FastAPI, PostgreSQL, and Docker, securing seed funding post-launch.
Designed a scalable cloud architecture on AWS (EC2, RDS, S3), reducing
operational costs by 28% and ensuring zero critical incidents in the first 6
months.
Integrated OpenAI API for automated content generation feature,
enabling the product to go to market faster without additional editorial
headcount.
Set up Docker Compose for local dev environments and GitHub Actions
pipeline for automated testing and deployment to AWS, reducing dev
onboarding from days to hours.
- 🇬🇧 English
- 🇺🇦 Ukrainian
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