Haseeb Shahid

Architected and deployed production AI applications serving 100,000+ users, building RAG pipelines and LLM integrations using LangChain and the OpenAI API. Designed and scaled LLM inference systems processing 500K+ API calls/day with caching, batching, and rate limiting to cut inference costs by 60%. Built multi-agent AI workflows (GPT-4, Claude) for automated content generation, customer support, and data analysis. Designed vector database architectures (Pinecone, Chroma) enabling semantic search and retrieval across 10M+ documents with sub-100ms query latency. Developed a prompt engineering and evaluation framework with structured testing against labeled outputs, improving response quality by 45%. Built back-end and infrastructure layers supporting AI features across 15+ enterprise applications (Node.js, Python/FastAPI, MongoDB, Redis) handling 10M+ requests/day at 99.9% uptime. Established CI/CD pipelines (GitHub Actions, AWS CodePipeline) reducing deployment time by 70%, and owned

Architected and deployed production AI applications serving 100,000+ users, building RAG pipelines and LLM integrations with LangChain and the OpenAI API. Designed and scaled LLM inference systems processing 500K+ API calls/day using caching, batching, and rate limiting to cut inference costs by 60%. Built multi-agent AI workflows to automate content generation, customer support, and data analysis. Designed vector database architectures (Pinecone/Chroma) powering semantic search across 10M+ documents with sub-100ms query latency. Developed a prompt engineering and evaluation framework with structured testing that improved LLM response quality by 45%. Built backend and infrastructure layers supporting AI features across 15+ enterprise applications using Node.js, Python/FastAPI, MongoDB, and Redis, handling 10M+ requests/day at 99.9% uptime. Established CI/CD pipelines and owned AWS infrastructure with auto-scaling and multi-region deployments.

Built backend infrastructure and API layers for 10+ production applications on the MERN stack and Python (Flask/Django), delivering full-stack solutions across diverse client needs. Developed and customized WordPress and Shopify sites for small business and e-commerce clients, including custom themes, plugins, and third-party integrations. Built e-commerce platforms with Stripe and PayPal supporting 25,000+ daily transactions across custom MERN store frontends and Shopify-based solutions. Optimized APIs to handle 1M+ requests/day using Redis caching and rate limiting, improved app performance by 50% through code splitting, lazy loading, and bundle optimization, and reduced database query times by 70% via indexing and connection pooling. Built multi-tenant SaaS applications with role-based access control and usage analytics, and deployed applications to AWS with automated backups and GitHub Actions CI/CD pipelines.