Cloud-Native IoT Monitoring & Automation Platform
Charter Communications · Senior Software Engineer
Charter Communications | IoT / Full-Stack Engineering / Cloud Platform
Contributed across the frontend, workflow automation layer, backend services, and cloud infrastructure for an R&D IoT platform that brought together device telemetry, environmental data, robotics-related integrations, and third-party APIs.
Overview
An R&D IoT monitoring and automation platform that connected device telemetry, environmental data, robotics-related integrations, and third-party APIs into a shared operational experience. Work spanned Vue.js dashboards, Node-RED workflow automation, Node.js and AWS Lambda backend services, and infrastructure-as-code for repeatable cloud environments.
My Contribution
- Built Vue.js dashboards for visualizing IoT telemetry, environmental indicators, device status, and integration data
- Developed Node-RED flows to connect devices, external APIs, event sources, and downstream automation actions
- Implemented backend services and AWS Lambda functions for data ingestion, transformation, orchestration, and API integration
- Contributed to infrastructure-as-code and cloud deployment workflows for repeatable R&D environments
- Integrated data from connected devices, environmental platforms, and external systems into a shared operational experience
- Worked in a fast-moving R&D environment where new integrations and prototypes were continuously evaluated and incorporated
Technical Architecture
The frontend presented normalized device and environmental data through Vue.js dashboards. Node-RED acted as an integration and workflow layer for connecting devices and third-party APIs, while AWS Lambda handled backend processing and cloud-side automation. Infrastructure was defined as code to support repeatable deployment of experimental and production-adjacent workloads.
Engineering Challenges
- Integrating inconsistent device and third-party API payloads
- Presenting telemetry clearly in dashboards
- Rapidly connecting new devices and services
- Separating visual workflow logic from backend processing
- Supporting experimentation without tightly coupling the platform
- Maintaining repeatable cloud environments
Reliability and Confidentiality
R&D IoT platforms combine heterogeneous device feeds and external APIs, so public documentation stays intentionally general. This portfolio omits internal product names, device identifiers, proprietary integration details, confidential visuals, and unsupported scale or uptime claims.
Technologies
- Vue.js, JavaScript, Node.js, REST APIs
- Node-RED for workflow and device/API integrations
- AWS Lambda for backend processing and cloud-side automation
- Infrastructure as Code for repeatable R&D cloud environments
- IoT integrations across devices, environmental platforms, and external systems