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Building AI-enabled full-stack products that stay useful in production.
I'm Kubilay Uysal, a full-stack developer focused on TypeScript, Next.js, PostgreSQL, and AWS. Lately I've been leaning harder into AI applications: RAG systems, document-based chat, pgvector-backed retrieval, and product experiences that connect useful model output with reliable backend execution.
Delivery profile
AI product UI + cloud delivery
Primary focus
AI-enabled full-stack products
Recent build
AskMyDocs
Data layer
PostgreSQL, pgvector, retrieval
AI applications
Productizing RAG, document chat, and model-assisted workflows into usable interfaces.
Retrieval layer
PostgreSQL, pgvector, ingestion pipelines, and grounded answers over raw generation.
Cloud delivery
AWS, SST, serverless APIs, and the operational discipline needed to ship real products.
Profile
Kubilay Uysal
Focus
Full-stack engineering with strong TypeScript foundations and growing emphasis on AI applications, RAG, and document intelligence.
Recent build
AskMyDocs
Document-based chat with retrieval, pgvector search, and grounded AI responses over uploaded knowledge.
Contact
kubilayuysal@gmail.comI'm a full-stack developer moving deeper into AI-native product work.
My work sits between product experience and system design. I still care about strong interfaces and clean backend structure, but the direction I'm excited about now is AI products: document intelligence, retrieval-backed chat, pgvector-powered search, and full-stack systems where the model layer is useful because the rest of the architecture is reliable.
AI product thinking
I like AI features that solve a real knowledge or workflow problem, not novelty demos that collapse outside a controlled prompt.
Retrieval architecture
RAG, document ingestion, chunking, embeddings, and PostgreSQL + pgvector feel like practical foundations for grounded answers.
Full-stack execution
I want the same level of care across interface, API, storage, eval loops, and deployment instead of treating AI as a disconnected layer.
Current direction
I'm positioning myself for international full-stack roles where AI product development, retrieval-backed systems, and cloud execution all matter at the same time. AskMyDocs pushed that focus forward for me in a practical way.
The work I want to be hired for now.
Rather than listing placeholder job history, this section reflects the stack and problem space I'm actively leaning into: AI application engineering, retrieval-backed systems, and full-stack delivery that is useful in production rather than only impressive in a demo.
AI application development
Turning model capabilities into usable full-stack products with clear interfaces, grounded responses, and workflows people can actually trust.
Retrieval and knowledge systems
I'm especially interested in document ingestion, embeddings, PostgreSQL + pgvector, and the data design behind document-grounded chat.
Cloud-ready full-stack delivery
Next.js, TypeScript, AWS, SST, and newer AI-oriented workflows like Strands matter to me when they help ship something stable and maintainable.
Recent work and the systems I want to build more of.
AskMyDocs is the clearest signal of where I'm heading: AI products with real retrieval, useful interfaces, and backend structure that supports the model layer instead of fighting it.
Recent project
AskMyDocs
A document-based chat application where uploaded knowledge becomes searchable and answerable through retrieval instead of generic model recall.
Document chat
Vector retrieval
Grounded answers
Active focus
AI knowledge interfaces
Full-stack products that turn documentation, PDFs, and internal knowledge into conversational flows people can actually use.
Lower search friction
Contextual answers
Practical AI UX
Platform layer
Cloud-native AI delivery
Deploying AI-enabled applications with the same rigor as any other product: auth, API boundaries, storage, observability, and cost awareness.
Reliable release flow
Operational clarity
Scalable foundations
Full-stack capability
Developer tooling and product surfaces
Internal tools, admin flows, and polished product surfaces that support the AI or backend layer instead of feeling disconnected from it.
High-signal interfaces
Faster operations
Clean systems thinking
Looking for a full-stack developer with growing AI product depth?
I'm open to full-stack opportunities where AI applications, retrieval-backed systems, cloud architecture, and thoughtful frontend execution all matter.
Or write to me right here