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I build autonomous AI workforces that go beyond basic chatbots. Using 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 𝗮𝗻𝗱 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 orchestration, I transform messy data into production-ready intelligence that executes complex tasks. If you are struggling with unreliable LLM outputs, disconnected data silos, or manual workflows that are slowing your growth, you don't need a prompt engineer, you need a Systems Architect. Most "AI solutions" today are just wrappers that hallucinate or fail at scale. Don't follow that approach. 𝙃𝙤𝙬 𝙄 𝙃𝙚𝙡𝙥 𝙔𝙤𝙪 𝙎𝙘𝙖𝙡𝙚: ✅Agentic Orchestration: I design "Supervisor-Worker" hierarchies (LangChain/LangGraph) where specialized AI agents collaborate, critique, and execute tasks autonomously. ✅Production-Grade RAG: I build Retrieval-Augmented Generation systems that don't just search, they reason through your proprietary data (Vector DBs like Pinecone/Milvus) with high precision. ✅Full-Stack Reliability: I treat AI as part of a larger ecosystem. I build the robust backends (Python/FastAPI/Django) and fluid frontends (React) necessary to make AI usable for your team or customers. ✅Human-in-the-Loop (HITL): I implement safety "circuit breakers" for sensitive tasks, ensuring AI acts with guardrails and escalates to humans when necessary. 𝙈𝙚𝙖𝙨𝙪𝙧𝙖𝙗𝙡𝙚 𝙄𝙢𝙥𝙖𝙘𝙩 & 𝙍𝙚𝙨𝙪𝙡𝙩𝙨: ⭐ 2.4M Monthly Calls: Engineered an AI Front Desk system using a multi-agent pattern to route and resolve high-volume interactions. ⭐ 22% Reduction in Data Errors: Architected normalized API models for 15+ disparate legacy systems to ensure seamless data interoperability. ⭐ 65% Performance Boost: Migrated monolithic legacy infrastructures to modern headless architectures, drastically improving global scalability. ⭐ Agentic Reasoning: Developed systems capable of autonomously querying external databases to perform complex eligibility and logic checks. 𝙈𝙮 𝙏𝙚𝙘𝙝 𝙎𝙩𝙖𝙘𝙠: 🔘AI & LLMs: OpenAI (GPT-4o), Amazon Bedrock, LangChain, LangGraph, CrewAI. 🔘Backend & APIs: Python (FastAPI, Django), Node.js, PostgreSQL, Neo4j (GraphRAG). 🔘Frontend & Data: React, Tailwind CSS, ETL Pipelines, AWS/Docker. 𝗪𝗵𝗼 𝗧𝗵𝗶𝘀 𝗜𝘀 𝗙𝗼𝗿: I work with forward-thinking firms and mid-sized companies that need to move beyond AI prototypes and into scalable, revenue-generating production systems. 𝗪𝗵𝗼 𝗧𝗵𝗶𝘀 𝗜𝘀 𝗡𝗢𝗧 𝗙𝗼𝗿: I am a bad fit for clients looking for basic GPT wrappers or simple "scripting." I prioritize documentation-first, secure, and interoperable architecture. About Me: I am a Senior Architect with 5+ years of experience navigating the duality of high-stakes technical execution and complex problem-solving. My work is defined by "Precision-by-design", treating every line of code as a critical component in a larger machine. Ready to deploy a digital workforce that actually works? Let’s discuss your project.

𝗥𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗔𝗜 𝗱𝗼𝗲𝘀𝗻'𝘁 𝗰𝗼𝗺𝗲 𝗷𝘂𝘀𝘁 𝗳𝗿𝗼𝗺 𝗯𝗲𝘁𝘁𝗲𝗿 𝗽𝗿𝗼𝗺𝗽𝘁𝘀. 𝗜𝘁 𝗰𝗼𝗺𝗲𝘀 𝗳𝗿𝗼𝗺 𝗯𝗲𝘁𝘁𝗲𝗿 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴. 𝗜 𝗯𝘂𝗶𝗹𝗱 𝗔𝗜 𝘁𝗵𝗮𝘁 𝗲𝗮𝗿𝗻𝘀 𝗶𝘁𝘀 𝘄𝗮𝘆 𝗶𝗻𝘁𝗼 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻. First call is free — no pitch, just a conversation about what you need. I spent 5 years as a backend engineer at Walmart, Oracle, and VMware, building systems where reliability wasn't optional. Now I apply that same engineering discipline to AI — because the gap between a promising demo and a product your customers can depend on is almost always engineering work, not model work. Datalumina-certified AI Engineer, focused on production-ready RAG, LLM orchestration, and evaluation. I write about RAG, LLM evaluation, and production AI engineering — happy to share case studies and technical posts on our first call. ✦ 𝗪𝗵𝗮𝘁 𝗜 𝗯𝘂𝗶𝗹𝗱 • RAG assistants that cite their sources and gracefully say "I don't know" • Support chatbots grounded in your docs and ticket history — ones that actually resolve • Internal AI tools wired into your CRM, database, or Notion — the kind your team keeps using after week one • Python-based workflow automation that quietly runs the work no one wants to do manually ✦ 𝗛𝗼𝘄 𝗜 𝘁𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝗔𝗜 𝘄𝗼𝗿𝗸 • Retrieval and cost-optimization first, model second. • I evaluate before I promise — if I can't measure it, I won't claim it won't break • Guardrails from day one — not bolted on after the first embarrassing output • I match the tool to the problem — sometimes a scheduled script beats an AI agent, and I'll tell you when that's true ✦ 𝗧𝗼𝗼𝗹𝘀 𝗜 𝘄𝗼𝗿𝗸 𝘄𝗶𝘁𝗵 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀 • Python • SQL 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 • FastAPI • PostgreSQL • Redis queues 𝗔𝗜 / 𝗠𝗟 • OpenAI • Claude • Gemini • PydanticAI • LangChain 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 • PostgreSQL with pgvector and TimescaleDB • Semantic search, Hybrid search 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 • Python • Scheduled jobs 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 • Hetzner Cloud • AWS • Docker • Git ✦ 𝗛𝗼𝘄 𝘄𝗲'𝗹𝗹 𝘄𝗼𝗿𝗸 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿 • Our first call is free — we figure out what "done" looks like before I quote • I write down scope, tests, and acceptance criteria, so you always know where we stand • You'll get readable code, short docs, and a working demo — never a black box • I don't disappear at handoff — I'll help you through deployment and the first round of real-world fixes Tell me what you're trying to solve. I'll ask the right questions before quoting anything.