AWS Cloud Engineer

Location – Remote Employment type – Full Time Experience - 3+ Years About Us Princeton Critical Minerals (PCM) is a Princeton University spin-out developing SmartPond™ , a next-generation sensor and digital-twin platform to optimize brine evaporation ponds for sustainable mineral extraction. Our technologies Lilypad™, ELITE™, and SmartPond™ — enable faster evaporation, smarter water use, and lower environmental impact in one of the world’s most critical supply chains. We are seeking an AWS Cloud Engineer in India to build and maintain the backbone of our data pipeline — from IoT sensor networks in harsh environments to predictive models and realtime dashboards that inform operations across multiple mining ponds. This role is central to scaling our pilots in North and South America into robust, multi-site deployments. Key Responsibilities • IoT Data Pipeline: Develop and maintain cloud pipelines (AWS IoT Core → Kinesis/Lambda → S3/RDS → QuickSight/Grafana) to ensure reliable, secure ingestion of sensor data. • Automation : Implement CI/CD pipelines, monitoring, and automated error handling to minimize manual intervention. • Model Integration: Work with data scientists to containerize and deploy brine chemistry and evaporation models into production pipelines. • Dashboard Enablement: Support analytics and visualization tools by ensuring clean, structured, and timely data flow. • Scalability: Architect systems to expand from single-pond pilots to multi-pond, multisite operations. • AWS Reliability: Own AWS account health, cost optimization, and service uptime. • Collaboration: Partner with mechanical/electrical engineers, field staff, and external vendors to close the loop between hardware and cloud. Qualifications Must Have: • Master’s/PhD in water resource engineering, Civil Engineer, Cloud Engineer, or related field. • 3+ years of experience building cloud data pipelines (preferably IoT). • Strong expertise with AWS services (IoT Core, Kinesis, Lambda, S3, RDS, QuickSight). • Programming experience in Python and SQL. • Familiarity with containerization (Docker/ECS) and Infrastructure-as-Code (Terraform/CloudFormation). • Demonstrated experience with time-series data and automation. • Willingness to work during US business hours for real-time collaboration with operations and field teams Nice to Have: • Experience with environmental, hydrological, or sensor network data. • Experience with ML/AI deployment (e.g., AWS SageMaker, TensorFlow/PyTorch). • Knowledge of visualization tools (Grafana, Plotly Dash). • Comfort working in startup environments (hands-on, fast iteration, field deployment). • English is must, Spanish speaker will be a plus What We Offer • Competitive salary. • Opportunity to work on climate-critical technologies at the intersection of AI, IoT, and clean energy. • Collaborative startup culture with room to grow into leadership roles.