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codemaker1023/README.md

Senior AI Full-Stack Engineer · LLMs · RAG · Real-time Voice AI · Cloud Platforms


About Me

I'm a Senior AI Full-Stack Engineer with 8+ years of experience building production-grade, Python-based AI systems and scalable cloud platforms. I specialize in LLMs, RAG pipelines, vector databases, and real-time voice/speech-to-text applications.

My work spans the full stack from low-latency FastAPI backends and WebSocket streaming services to modern React/Next.js frontends and I've shipped systems trusted by thousands of users in healthcare, federal, and enterprise environments.

  • 🧠 Deep expertise in Generative AI, LangChain/LangGraph, and multi-agent workflows
  • 🎙️ Built real-time voice AI pipelines with Whisper, Deepgram, LiveKit, and ElevenLabs
  • 🏥 Delivered HIPAA-compliant clinical AI tools that cut documentation time by 40%
  • ☁️ Deployed at scale on AWS SageMaker/Bedrock, Azure OpenAI, and GCP Vertex AI

Tech Stack

Frontend

JavaScript TypeScript React Next.js React Native Tailwind CSS

Backend

Python FastAPI Flask Node.js NestJS Express.js WebSockets PostgreSQL MongoDB Supabase Firebase

AI & Machine Learning

OpenAI LangChain PyTorch TensorFlow Hugging Face Stable Diffusion RAG Vector DB

Voice & Conversational AI

Whisper Deepgram ElevenLabs LiveKit Amazon Polly

Cloud & DevOps

AWS Azure GCP Docker Vercel CI/CD


Highlights

  • 🏥 Built multimodal, voice-enabled AI clinical assistants (Whisper + Deepgram + LiveKit) serving 10,000+ monthly therapy sessions
  • 📄 Generated SOAP notes & session summaries that reduced clinician documentation time by 40%
  • 💰 Reduced AI inference costs by 40% deploying on AWS SageMaker + Bedrock at millions of monthly requests
  • 🔒 Designed HIPAA-compliant voice & text pipelines with PHI-safe data architecture
  • 🏛️ Modernized federal facility management systems tracking 5,000+ assets across multi-site operations
  • ⚡ Delivered low-latency real-time transcription and concurrent audio sessions at production scale
  • 📈 Accelerated triage workflows and reduced provider documentation time by 30–45% with LLM-powered clinical tools

Let's Connect

"Building reliable AI systems that solve real problems at production scale."

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