Guilherme Balduino Lopes

• Designing and architecting high-performance microservices using Golang and Python tailored for the telecommunications sector.
• Architecting scalable AIoT ecosystems from the ground up to handle high-throughput, low-latency communication between distributed IoT devices and cloud infrastructure.
• Developing robust real-time firmware solutions using C++ and ESP-IDF, ensuring secure, optimized, and efficient data ingestion pipelines optimized for downstream AI processing.
• Leading the strategic integration of Edge AI initiatives and defining the technical roadmap to embed intelligence directly into IoT hardware constraints.

• Managed the entire deployment and lifecycle of an active fleet of over 1,500 IoT devices, architecting backend features in Golang and Python across 7 distinct product models.
• Engineered real-time embedded firmware in C/C++ to ensure resilient edge connectivity utilizing MQTT, LoRaWAN, Wi-Fi, and 4G/LTE protocols.
• Developed automation workflows and scalable backend APIs using Python (Flask) and Go to optimize system observability and network operations monitoring.
• Utilized ESP-IDF and PlatformIO environments for firmware development, contributing directly to the physical deployment of 5 new IoT hardware lines.

• Automated legacy industrial hardware setups by engineering a custom remote IoT gateway using Python, Modbus TCP, and MQTT pipelines.
• Deployed event-driven, serverless data pipelines on AWS using Lambda, DynamoDB, and AWS IoT Core for real-time telemetry processing.

Specialization focused on building production-grade AI systems. Core curriculum covers LLM architectures, advanced fine-tuning, autonomous agents, Model Context Protocol (MCP), MLOps pipelines, cloud scalability, and data governance.

Core coursework in control systems, real-time automation, robotics, analog/digital electronics, industrial communication protocols, and embedded systems design.