Full Stack Developer | React, Node.js, Python, AI Systems

I build production AI systems and full-stack SaaS platforms for high-stakes industries. Not prototypes. Deployed systems with real users, real data, and real consequences for getting it wrong.

My core expertise is RAG architecture and LLM integration. I have designed and shipped retrieval-augmented generation pipelines from scratch using Python, LangChain, LlamaIndex, pgvector, and the Claude and OpenAI APIs. My systems handle the full pipeline: document ingestion, intelligent chunking strategies, embedding generation, HNSW-indexed vector search, hybrid retrieval, re-ranking, and structured output generation enforced through Pydantic schema validation. I build RAG systems that are production-reliable, not just functional in a notebook.

On the full-stack side I architect multi-tenant SaaS platforms with normalized PostgreSQL schemas, role-based access control across multiple user tiers, REST and GraphQL APIs with structured validation, React and Next.js frontends with TypeScript, and cloud deployments on AWS, Vercel, and Render. I have built Stripe subscription billing systems, webhook-driven workflows, OAuth 2.0 authentication flows, and CI/CD pipelines that reduce deployment time significantly.

My AI engineering experience includes multi-agent orchestration using CrewAI and LangChain, real-time data ingestion pipelines, Pydantic V2 output contract enforcement, LangSmith observability, and semantic search systems using both OpenAI embeddings and open source sentence transformers. I have worked with GPT-4o, Claude 3.5, and Llama 3 in production environments and understand the tradeoffs between models for different use cases.

My production work spans legal-tech, logistics intelligence, AI workflow automation, and cybersecurity visualization. I built Trust Terra, a secure multi-tenant legal-tech SaaS platform with a full RAG pipeline for AI-assisted document drafting. I built Supply Chain Sentinel, an autonomous multi-agent AI system that monitors global logistics disruptions and delivers structured intelligence reports in real time. I have contributed to Composio, an open source AI integration framework, delivering logistics parsing utilities with 100% Pytest coverage and Pydantic V2 schema enforcement.

I understand GDPR-compliant data architecture from the ground up: data minimization, purpose limitation, right to erasure, row-level security, and the infrastructure implications of EU-based cloud deployment. This is directly relevant for European clients building consumer or enterprise AI products that handle personal data.

I work with European clients remotely and am experienced with async communication across time zones. I deliver clean, well-documented, production-ready code with clear handoff documentation.

If you are building an AI-powered product, a document intelligence system, a multi-tenant SaaS platform, or a backend integration, I am the engineer you are looking for.