Presentation
I am a Full-Stack AI Engineer specializing in building scalable web apps and intelligent AI features. With 8+ years of experience, I combine React/Next.js frontends, Node.js and Python backends, and advanced LLM integrations using Claude and OpenAI to deliver RAG systems, AI agents, and automated solutions that drive measurable business results.
• Architected 6 production RAG systems with Claude 3.5 and vector databases, delivering 4x faster retrieval and 90%+ relevance.
• Shipped 10+ high-performance Next.js applications with TypeScript and Tailwind achieving 98+ Lighthouse scores.
• Built scalable backends using FastAPI and NestJS that processed millions of requests at sub-50ms latency.
• Implemented hybrid RAG pipelines with reranking and hallucination controls for reliable LLM-powered features.
• Developed n8n workflows and custom AI agents that saved clients over 25 hours per week in manual processes.
• Managed AWS infrastructure with Docker, Kubernetes, and CI/CD enabling daily reliable deployments.
• Mentored teams on prompt engineering, LLM evaluation, and clean full-stack development practices.
In the frontend, I create fast, accessible interfaces using Next.js server components, Zustand for state, TanStack Query, Tailwind CSS, and shadcn/ui. I optimize for Core Web Vitals, SEO, and inclusive design across devices.
For backend and AI, I develop high-performance APIs with FastAPI and NestJS, design RAG architectures with LangChain, pgvector, and Pinecone, and ensure security, cost efficiency, and observability. I leverage PostgreSQL, Prisma, Supabase, and Redis for data layers while integrating Claude and OpenAI responsibly.
On the cloud side, I architect solutions on AWS and Vercel using Infrastructure as Code, container orchestration, and robust monitoring. I follow agile processes, collaborate closely with stakeholders, and deliver projects that exceed expectations. I am currently available for new Upwork engagements and would welcome the opportunity to discuss how I can contribute to your AI-powered product goals.
Best regards,
Oliwier
Background
- Implemented basic features like forms, data grids, database connections, and file handling.
- Fixed bugs and improved UI responsiveness in existing desktop applications.
- Learned Git, code review processes, and basic installers for desktop deployment.
- Gained foundational experience in desktop application development, client communication, and delivering production software.
• I built and maintained Node.js REST APIs and later introduced Python/FastAPI services for data analytics pipelines.
• I integrated payment gateways (Stripe) and email services while ensuring GDPR-compliant data handling.
• I participated in code reviews, fixed critical bugs, and helped migrate parts of the codebase to TypeScript.
• I optimized PostgreSQL queries and reports, reducing generation time for key dashboards by 60%.
• I containerized development environments with Docker to streamline onboarding for new team members.
• Developed and scaled FastAPI microservices to ingest and process Stripe webhooks, calculate complex MRR and churn metrics, and serve real-time updates to over 2,000 paying customers.
• Designed PostgreSQL data models and performed heavy query optimization with SQLAlchemy, reducing average report generation time from 8 seconds to under 1.5 seconds.
• Added early AI prototype features using Anthropic Claude to detect subscription anomalies and surface intelligent alerts, which later became a key product differentiator.
• Introduced Docker containerization and GitHub Actions CI/CD pipelines that improved deployment reliability and reduced release-related incidents by 70%.

