Tahir H.

Most AI projects never make it to production. They demo well, get approved, then fall apart the moment real users, real data, and real failure modes hit. The difference is not the model. It is the engineering around it. 𝗜 𝘄𝗼𝗿𝗸 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗹𝘆. I am an AI Engineer building production voice agents, multi-agent systems, and full-stack AI SaaS. I ship systems that hold up under real load, not prototypes that impress in a demo. Every system I build has error handling, recovery paths, audit logging, and a clear answer to what happens when something fails. That is the difference between a demo and a product. 𝗪𝗵𝗮𝘁 𝗜 𝗕𝘂𝗶𝗹𝗱 𝗩𝗼𝗶𝗰𝗲 𝗔𝗜 & 𝗧𝗲𝗹𝗲𝗽𝗵𝗼𝗻𝘆 Inbound and outbound voice agents handling thousands of concurrent calls. Speech-to-text, conversational orchestration, text-to-speech, human transfer with failed-transfer recovery, and CRM write-back in real time. Deployed in healthcare, automotive, and home services. 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 & 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 Graph-based orchestration with human-in-the-loop approval gates. Multi-agent systems for CPA firms, closed-loop advertising optimization, and enterprise document intelligence. Every action logged with reasoning, every risky decision gated on approval. 𝗥𝗔𝗚 & 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 Retrieval pipelines over documents, spreadsheets, and web sources with source citations on every answer. Hallucination resistance built in from day one. Vector databases, hybrid search, structured outputs. 𝗙𝘂𝗹𝗹-𝗦𝘁𝗮𝗰𝗸 𝗔𝗜 𝗦𝗔𝗔𝗦 Multi-tenant platforms with row-level security, role-based access, subscription billing, and admin dashboards. Next.js front end, Python or Node backend, PostgreSQL, deployed on cloud infrastructure. 𝗠𝗼𝗯𝗶𝗹𝗲 𝗔𝗽𝗽𝘀 React Native and Expo for iOS and Android. Built a consumer app from scratch that scaled to 100,000+ users in three months. Subscription billing, real-time features, push notifications, app store deployment. 𝗪𝗵𝗼 𝗜 𝗪𝗼𝗿𝗸 𝗪𝗶𝘁𝗵 Healthcare and HIPAA-regulated platforms, fintech and financial services, automotive and dealership networks, legal and compliance, e-commerce and marketplace SaaS, real estate and mortgage, enterprise operations. Founders and teams building serious AI products who need a senior engineer who will tell them the right approach before agreeing to build it, and who will document the architecture so they own the system after handover, not just the code. 𝗦𝘁𝗮𝗰𝗸 & 𝗧𝗼𝗼𝗹𝘀 Voice AI: telephony, speech-to-text, text-to-speech, conversation orchestration Agent frameworks: graph-based and chain-based orchestration, custom multi-agent systems LLM & RAG: commercial and open model providers, vector databases, structured outputs, tool calling Full-stack: Next.js, React, TypeScript, Python FastAPI, Node.js, Supabase, PostgreSQL, Redis Automation: n8n, Make, Zapier Infrastructure: AWS, Vercel, Docker, CI/CD pipelines AI coding: Claude Code, Cursor If you are building something in voice AI, agentic systems, or production SaaS and want someone who will tell you honestly what the right approach is before agreeing to build it, send me the brief and I will tell you exactly how I would approach it. 𝗞𝗲𝘆𝘄𝗼𝗿𝗱𝘀 AI engineer · voice AI developer · AI agent development · multi-agent systems · LangGraph · LangChain · RAG pipeline · retrieval augmented generation · LLM engineer · OpenAI API · Anthropic Claude · Python · FastAPI · Next.js · React · TypeScript · Supabase · PostgreSQL · AWS · Twilio · n8n · Make · prompt engineering · HIPAA-compliant AI · multi-tenant SaaS · production AI systems · conversational AI · AI chatbot development · AI automation