Hire the Best Internet of Things Specialists
in Saudi Arabia

I'm Shoaib Siddique, an electronics engineer and full-stack systems developer with over 9 years of experience in embedded systems, IoT product development, and cloud-integrated software solutions. I specialize in building intelligent hardware prototypes and complete IoT ecosystems—from PCB design and firmware to Python-based dashboards and backend APIs. Whether you're a startup building a new product or an enterprise needing robust automation or monitoring solutions, I can help bring your concept to life. Core Capabilities: - PCB Design & Circuit Simulation (Altium, KiCAD) - Embedded Systems (ESP32, STM32, Arduino, Raspberry Pi) - Communication Protocols (RS485, UART, SPI, LoRa, BLE, DALI) - Cloud-Based IoT (AWS/GCP, MQTT, REST APIs) - Firmware Development (C, C++, Micropython) - Python Desktop & Web Apps (Tkinter, Streamlit, Flask) - Remote Troubleshooting, Testing & Prototyping (own lab) Let’s build innovative, scalable, and cost-efficient solutions that blend electronics with intelligent software. Available for consultations, long-term collaboration, or rapid prototyping.

Senior Embedded Systems & IoT Engineer | 9+ Years of Innovation I am an Embedded Systems Engineer with deep expertise in industrial IoT, ultra-low power design, and multi-protocol connectivity solutions. My career spans from foundational embedded systems to cutting-edge industrial applications, with a proven track record of delivering breakthrough performance in power optimization and system reliability. Notable Achievements: - 4+ year battery life on LoRaWAN devices (industry-leading performance) - Sub-2µA sleep current optimization in production systems - Safety-critical systems for mining vehicle environmental control - Multi-protocol IoT platforms with adaptive connectivity (WiFi → NBIoT → LoRaWAN) Core Technical Expertise: Industrial IoT & Connectivity: - LoRaWAN protocol mastery with adaptive network joining strategies - Multi-protocol systems: WiFi, NBIoT BG95, Bluetooth LE, CAN Bus - AWS IoT Core integration with SSL/TLS, Lambda functions, and OTA updates - Protocol conversion and data normalization across SigFox, LoRaWAN, and TCP devices Ultra-Low Power Design: - Hardware power leak detection and mitigation techniques - Advanced sleep mode optimization (<2µA achievement) - Battery life modeling and power consumption analysis - Real-time power profiling with tools like Otii-Arc System Architecture & Integration: - Distributed CAN bus systems for safety-critical applications - Computer vision integration with OpenCV for industrial automation - Complex queuing systems with reverse-engineered protocol integration - Medical device development with motion tracking algorithms Development Platforms & Tools: - MCUs: Silabs EFR32, Nordic nRF52, ESP32, STM32, PIC, ATmega series - Languages: C/C++, Python, JavaScript (for IoT data converters) - Cloud Platforms: AWS IoT Core, S3, Lambda functions - Development: SDK development, driver implementation, RTOS integration Industry Experience: - Mining & Industrial Safety: Environmental monitoring and control systems - Healthcare IoT: Motion tracking devices with IMU sensor fusion - Smart Infrastructure: Parking systems, inventory management, production monitoring - Home Automation: Multi-protocol mesh networking and control systems Professional Approach: I excel at transforming complex technical challenges into elegant, production-ready solutions. My experience spans the complete product lifecycle from concept to deployment, including hardware bring-up, firmware development, cloud integration, and field optimization. I've successfully collaborated with international teams and delivered solutions across diverse industries.

Most AI projects are impressive demos that collapse in production. I build the architectures that do not handle edge cases, eliminating hallucinations, and scaling reliably from day one. With 11 years of engineering experience, I specialize in the hard side of AI, rigorous model research, production grade system design, and full stack delivery. I do not just prompt models or wrap APIs. I build the data pipelines, memory structures, retrieval systems, and guardrails that make AI reliable enough for real business use. GENERATIVE AI & ADVANCED RAG Simple vector search is rarely enough. I engineer RAG systems that actually work in production: • Hybrid Search: combining semantic understanding with keyword precision for accurate, citation backed answers with near zero hallucinations • Semantic chunking and re ranking algorithms to ensure the model reads the right context before answering • Fine-tuning LLaMA 3, GPT, and Claude on proprietary data for domain-specific accuracy • Multi agent workflows using LangGraph and CrewAI agents that query SQL databases, browse the web, and trigger API workflows autonomously, with planning logic that keeps them on track • Production & cost optimization: caching layers and prompt compression strategies that reduce LLM API costs by 30 to 40% while improving speed • Tools: LangChain, LangGraph, CrewAI, OpenAI, Anthropic , Pinecone, Weaviate, ChromaDB, FAISS COMPUTER VISION & DEEP LEARNING For cases where off the shelf models fall short: • Custom CNNs and Vision Transformers for manufacturing defect detection, medical imaging, and document analysis • Real time object detection and tracking via YOLO, OpenCV, with WebSocket and Edge AI pipelines for live video streams and low latency market data • Model optimization: quantization, pruning, and performance tuning to run heavy models efficiently on edge devices or at cloud scale • Tools: PyTorch, TensorFlow, OpenCV, CUDA, Hugging Face Transformers, MediaPipe AI RESEARCH & MODEL EXPERIMENTATION When standard solutions don't give you the accuracy you need: • Rigorous model evaluation on real-world datasets with reproducible, well documented experiments • Performance benchmarking and ablation studies to identify what actually moves the needle • Turning research outcomes into clean, maintainable production code your team can scale confidently FULL STACK AI DELIVERY I bridge the gap where most AI engineers fail, connecting research grade backends to real user interfaces: • Frontend: Next.js (App Router), React, TypeScript, Tailwind CSS, D3.js instant load dashboards and data UIs • Backend: FastAPI, Django, Node.js robust Python APIs that handle data processing securely at scale • Real time systems: WebSockets and edge pipelines for live data without latency • DevOps: Docker, Kubernetes, AWS auto scaling infrastructure that survives traffic spikes CORE TECH STACK AI/ML: PyTorch · TensorFlow · Hugging Face · CUDA · Scikit learn · XGBoost GenAI: OpenAI · Anthropic Claude · LLaMA-3 · Mistral · Gemini Orchestration: LangChain · LangGraph · CrewAI · LlamaIndex Vector DBs: Pinecone · Weaviate · ChromaDB · FAISS Computer Vision: OpenCV · YOLO · MediaPipe · Albumentations Full Stack: Next.js · React · TypeScript · FastAPI · Django · Node.js DevOps: Docker · Kubernetes · AWS If you are tackling a hard problem that requires more than a plug and play solution, whether that is a production RAG system, a custom vision model, or a full AI powered SaaS, invite me to your job. Let's engineer something that actually works.