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𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀𝗲𝘀 𝗱𝗼𝗻'𝘁 𝗻𝗲𝗲𝗱 𝗺𝗼𝗿𝗲 𝗔𝗜 𝘁𝗼𝗼𝗹𝘀. 𝗧𝗵𝗲𝘆 𝗻𝗲𝗲𝗱 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝗿𝗲𝗱𝘂𝗰𝗲 𝗺𝗮𝗻𝘂𝗮𝗹 𝘄𝗼𝗿𝗸, 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝘁𝗵𝗲𝗶𝗿 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀, 𝗮𝗻𝗱 𝗵𝗲𝗹𝗽 𝘁𝗲𝗮𝗺𝘀 𝗱𝗼 𝗺𝗼𝗿𝗲 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗵𝗶𝗿𝗶𝗻𝗴 𝗺𝗼𝗿𝗲 𝗽𝗲𝗼𝗽𝗹𝗲. I'm an AI Systems Architect and OpenClaw Specialist with 3+ years of experience building AI agents, business automation systems, RAG solutions, and full-stack AI applications that run reliably in production. 𝗪𝗵𝗮𝘁 𝗜 𝗰𝗮𝗻 𝗵𝗲𝗹𝗽 𝘄𝗶𝘁𝗵: - AI Agents and Task Automation - Business Workflow Automation - OpenClaw Setup and Custom Development - RAG and Internal Knowledge Systems - Full-Stack AI Applications - API Integrations and System Connectivity - Internal Tools and Operational Dashboards - MCP Servers and Custom Tool Integrations 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗲𝘀 𝗜 𝘄𝗼𝗿𝗸 𝘄𝗶𝘁𝗵: - E-commerce and SaaS my main focus - Also work with agencies, logistics, real estate, and more 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗺𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁: - I focus on solving real business problems, not adding unnecessary complexity - I take projects from planning all the way to deployment - I build things that teams can actually use every day - I hold relevant certifications in AI and cloud technologies - You can see my work in action live demos available on request 𝗥𝗲𝗰𝗲𝗻𝘁 𝘄𝗼𝗿𝗸 𝗶𝗻𝗰𝗹𝘂𝗱𝗲𝘀: - Built AI agents that helped teams handle the workload of 3-5 extra people without expanding the team - Developed OpenClaw assistants that use tools, remember context, and complete tasks across workflows - Created internal document and knowledge search systems - Built full AI applications from planning and design to live deployment - Connected AI systems with APIs, databases, and existing business software 𝗖𝗼𝗿𝗲 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀: OpenClaw • Python • FastAPI • LangChain • LangGraph • RAG • PostgreSQL • React • Next.js • Node.js • TypeScript • Docker • OpenAI • Claude • MCP 𝗟𝗲𝘁'𝘀 𝗧𝗮𝗹𝗸: If you want to automate your operations, reduce manual work, or build an AI-powered system , send me a message and let's get it built.

I build AI systems that don’t break in production, don’t crumble at scale, and don’t become your next expensive rewrite. Over the past year I've shipped a voice AI healthcare assistant handling 50,000+ users (cutting staff workload by 70%), built agentic workflows for real-time patient triage and scheduling, and developed LLM infrastructure that runs in live enterprise environments. I currently build tooling for enterprise companies including a platform for deploying and scaling AI models in production. My core stack: → Voice & Real-Time AI: LiveKit, Deepgram, Cartesia → Agentic Systems: LangChain, OpenAI API, multi-agent orchestration → LLM Deployment: vLLM, Ollama, Hugging Face, GPU inference, CUDA → Full-Stack: React.js, Next.js, FastAPI, Django, Node.js → DevOps / Infra: Docker, Kubernetes, Grafana, Linux, Slurm What I build: - AI voice agents for customer-facing and healthcare use cases - Agentic automation pipelines (lead generation, triage, scheduling) - LLM infrastructure including both local and cloud deployment, inference optimization - Full-stack AI-powered applications with real backend systems - GPU clusters and HPC environments for AI research I've been awarded First Prize at the National Tech Expo for edge AI systems and built a 1.2 petaflop GPU cluster for AI research from scratch. If you need AI that integrates cleanly into real operations and delivers measurable output; let's talk.

Computer Vision Engineer specializing in real-time detection systems across surveillance AI, manufacturing inspection, medical imaging, and smart city infrastructure — deployed to production. I build end-to-end: camera input, model training, TensorRT optimization, edge or cloud deployment, and backend integration. Not prototypes. Working systems. WHAT I HAVE SHIPPED: Multi-tenant AI surveillance platform with 8 real-time detection agents — intrusion, loitering, occupancy, vehicle counting, LPR, fire/smoke detection, entry after hours, and late checkout. YOLO11s + PaddleOCR on RunPod GPU, RTSP stream management via MediaMTX, FastAPI backend on DigitalOcean, CI/CD via GitHub Actions with a self-hosted runner. Supabase for auth and Postgres. Full production deployment. Spine X-ray segmentation system — 25-class vertebrae labeling (C1 through L5) with automated clinical metric extraction: disc height, segment angle, neutral listhesis, interspinous gap. Dual architecture: ResNet34 U-Net baseline and a custom ConvNeXt-Tiny encoder with CBAM attention trained on real X-rays and synthetic DRR data from CT volumes. 0.92 Dice on full-spine segmentation. Real-time defect detection on NVIDIA Jetson Xavier for a food and beverage production line. TensorRT FP16 inference, zero cloud dependency, PLC integration for automated pass/fail. Defect catch rate improved significantly over manual baseline. LiDAR-camera sensor fusion pipelines for smart city traffic monitoring — ROS, DeepStream, NVIDIA Jetson, production-deployed infrastructure. CORE CAPABILITIES: → Detection, segmentation, tracking: YOLO variants, SAM2, custom PyTorch → TensorRT optimization: FP16/INT8 quantization, ONNX export, engine serialization → Edge deployment: Jetson Nano, NX, Orin, Xavier — hardware bring-up to production → Medical imaging: U-Net architectures, multi-class segmentation, DICOM, clinical metrics → Surveillance AI: multi-agent detection, RTSP streams, LPR, event-based alerting → Industrial integration: FastAPI, MQTT, EMQX, Azure IoT Hub, AWS S3, Docker, Supabase INDUSTRIES: Manufacturing quality control — food and beverage, general production lines Surveillance and security — multi-camera platforms, license plate recognition, event detection Medical imaging — vertebral segmentation, clinical measurement pipelines Smart city and traffic — LiDAR-camera fusion, intrusion detection, infrastructure monitoring I communicate clearly, surface blockers early, and deliver systems that run reliably in your environment.

I am a Software Engineer specializing in enterprise data infrastructure and large-scale web automation systems. With 4+ years of engineering experience, I architect robust, maintainable data pipelines that power business intelligence at scale. 🎯 Core Competencies: • ETL Architecture: Designing production-grade data pipelines (Python/TypeScript) with automated validation, schema enforcement, and error handling • Anti-Detection Engineering: Bypassing enterprise-grade protections (Cloudflare, Akamai, DataDome) with 95-99% success rates • Data Infrastructure: Building distributed scraping architectures capable of handling 10M+ daily requests with auto-scaling, queue management, and real-time monitoring • Cloud Integration: Seamless data delivery to BigQuery, PostgreSQL, AWS S3, Snowflake, and data warehouses with optimized loading strategies 🛠 Technical Stack: • Languages: Python (Scrapy, AsyncIO), TypeScript/Node.js • Automation: Selenium Grid, Puppeteer Cluster, Playwright with stealth plugins • Data Engineering: Apache Airflow, dbt, Pandas, custom ETL frameworks • Infrastructure: Docker, Kubernetes, Redis, RabbitMQ, rotating residential proxies • Storage: BigQuery, PostgreSQL, MongoDB, AWS S3, Google Cloud Storage 💼 Ideal For: • Companies needing reliable, long-term data extraction infrastructure • ETL pipeline development and data warehouse integration • Complex automation requiring custom browser engineering • High-volume scraping requiring distributed worker architectures and SLA guarantees Why Enterprise Clients Choose Me: ✓ Engineering-First Approach: I write clean, documented, version-controlled code not brittle scripts ✓ Scalability by Design: Systems built to grow from thousands to millions of records without rewrites ✓ Data Integrity: Automated quality checks, deduplication, and schema validation at ingestion ✓ DevOps Ready: CI/CD integration, containerized deployments, and comprehensive logging

𝗠𝗼𝘀𝘁 𝗔𝗜 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗴𝗲𝘁 𝗯𝘂𝗶𝗹𝘁 𝘁𝘄𝗶𝗰𝗲: once as a prototype, and again when they break in production. I build them once. I specialize in shipping OpenAI and LLM integrations inside production-grade full-stack systems - NestJS backends, Django APIs, React frontends - deployed on AWS with automated CI/CD pipelines and zero failed handoffs. 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗹𝗼𝗼𝗸𝘀 𝗹𝗶𝗸𝗲 𝗶𝗻 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲: - 200+ store Dutch retailer - automated product enrichment via OpenAI Vision API, zero failed deployments (TerStal) - 90% faster SEO task execution through AI-driven automation on a high-traffic SaaS platform (SearchAtlas) - 31-module NestJS oncology backend with real-time dashboards and strict multi-hospital data isolation (VOP) - Enterprise WordPress hosting scaled to thousands of sites, 90+ Google PageSpeed score (BionicWP) - 99%+ uptime maintained on a production staffing platform under active scale (EngineHire) 𝗜 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝘁𝗵𝗿𝗲𝗲 𝘁𝗵𝗶𝗻𝗴𝘀: clean architecture, cost-optimized AI pipelines, and deployments that don't fail. If you are 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗻 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗦𝗮𝗮𝗦 and need someone who handles the 𝗳𝘂𝗹𝗹 𝘀𝘁𝗮𝗰𝗸 𝗳𝗿𝗼𝗺 𝗟𝗟𝗠 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 to production infrastructure, let's talk.

Availability: Full-time freelancer, 𝟰𝟬+ hours/week, open to long-term collaborations. I’m a Full-Stack & AI Engineer with 10+ years of experience building web and mobile applications and 3+ years of specialized experience in AI and Large Language Models (LLMs). I design, develop, and deploy production-grade platforms, from scalable SaaS dashboards to AI-powered assistants, RAG systems, and voice agents. I work end-to-end: architecture → backend → frontend → cloud deployment, with a focus on clean code, maintainable systems, and high performance. Over the past few years, I’ve delivered solutions that integrate AI/LLM pipelines, vector search, real-time chat, and voice agents for enterprise and startup clients. 🤖 AI & LLM Expertise - MCP Server Development: Designing and integrating custom MCP servers for AI agents, enabling structured tool usage, external system integrations, database querying, and API orchestration. - Fine-Tuning: Persona creation, Q&A systems, and domain-specific models (medical, legal) using Mistral and Llama 3. - Synthetic Dataset Generation: Streamlining LLM training with high-quality datasets. - Evaluation Frameworks: Assessing LLM performance with custom metrics. - Cloud Deployment: Deploying LLMs on AWS and GCP. - AI Agents & Voice Bots: Proficient with LiveKit, Retail AI, OpenAI. - Open-Source Deployment: Expertise deploying models like vLLM on AWS/GCP/RunPod using SkyPilot. 🛠️ 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗧𝗼𝗼𝗹𝘀 & 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 ➜ LLM Tools: LangChain, Langsmith, Langfuse , Hugging Face, Transformers. ➜ Vector Databases: Chroma, FAISS, Pinecone, Qdrant , Opensearch ➜ AI Workflows: Flowise AI, LangFlow, StackAI. 🛠️ 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 ➜ Languages & Frameworks: Python, Node.js, ReactJS. ➜ Database Management: MongoDB, MySQL, PostgreSQL , Supabase , FIrebase ➜ Frontend & Backend Integration: Seamlessly connecting APIs and user interfaces. 🌟 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗦𝗸𝗶𝗹𝗹𝘀 ➜ Open-Source LLMs: Proficiency in LLAMA 3, Mistral 7B, and Mixtral 8x7B. ➜ Prompt Engineering: Expertise in techniques like Chain of Thought, Few-shot Prompting, and Self-Reflection. ➜ Fast Inference: Implementing high-speed solutions with vLLM . 🌟 𝗪𝗵𝘆 𝗖𝗵𝗼𝗼𝘀𝗲 𝗠𝗲? With over 10 years of experience, I deliver scalable, cutting-edge solutions tailored to your project’s needs. Whether it's advanced AI models, MCP server development, LLM optimization, or full-stack development, I ensure top-notch results every time. Let’s collaborate to bring your ideas to life!