Industrial AI Systems Engineer focused on Edge Computer Vision deployments, automated quality inspection pipelines, and distributed Generative AI architectures. Specialist in architecting enterprise Retrieval-Augmented Generation (RAG) systems, vector database indexing, and event-driven data streaming bridging industrial field telemetry with high-performance backends.
- edge-vision-inspector Real-time automated optical inspection (AOI) pipeline designed for factory floor sorting and anomaly detection.
- Tech: OpenCV, YOLO, PyTorch, Python, TensorRT, MQTT.
- plc-telemetry-gateway High-throughput data ingestion service streaming Modbus/OPC-UA telemetry into event brokers and analytics engines.
- Tech: Python, FastMCP, WebSockets, Redis Streams, Docker.
- industrial-rag-pipeline Multi-layer semantic RAG framework capable of indexing technical manuals, blueprints, and operational logs with hybrid lexical/vector search.
- Tech: LangChain, Qdrant Vector DB, FastAPI, PostgreSQL, Ollama/Local LLMs.
- vision-agent-orchestrator Autonomous inspection agent integrating multimodal LLMs with live camera feeds for contextual decision making and automated incident reporting.
- Tech: Python, AsyncIO, PyTorch, FastMCP, JSON-RPC.
Computer Vision & AI : OpenCV, PyTorch, YOLO, TensorRT, MediaPipe, Edge AI
Generative AI & RAG : LangChain, RAG Architectures, Qdrant, ChromaDB, Context Engineering, Local LLMs
Languages : Python, C/C++, TypeScript, JavaScript, SQL, Bash Scripting
Backend & Pipelines : FastAPI, Django, Redis, WebSockets, Message Queues, AsyncIO
Industrial & Edge : Linux (Debian/Arch), Docker, Proxmox, MQTT, Industrial Telemetry, IPC
Databases & Storage : PostgreSQL, Qdrant Vector DB, Redis Cache, SQLite, Time-Series DBs
- GitHub: @elonesampaio
- LinkedIn: linkedin.com/in/elonesampaio
- Email: elone@izatacore.com