AI ENGINEER - Industrial Water Analytics

ResponsibilitiesAI & Data EngineeringDesign and implement AI-powered pipelines for industrial water applications such as:Sensor anomaly detectionWater quality prediction and sensor drift detectionPredictive maintenance for pumps, valves, and metersDevelop predictive machine learning and time-series analytics pipelines for high-frequency sensor dataBuild and maintain feature engineering pipelines for physical and hydraulic signalsIoT & Systems IntegrationIntegrate AI Agents with IoT platforms, SCADA systems, and edge devicesDeploy models across cloud and edge environments (containerized or embedded)Collaborate with domain experts, firmware and hardware teams to translate operational requirements to AI-driven solutionsOptimize models for latency, reliability, and efficiencyCloud & Agentic AI WorkflowsIntegrate AI agents with IoT sensors and cloud data platforms.Develop AI-driven data analysis, anomaly detection, root-cause analysis, and recommendation engines for water operationsImplement Retrieval-Augmented Generation (RAG),knowledge graphs, and LLM-based decision-support systemsDeploy AI services using cloud platforms (e.g., Azure, AWS, or equivalent)Design APIs and data services for real-time and batch inferenceMonitor workflow performance and data quality in productionApplied Research &InnovationApply physics-informed ML, hybrid models, or graph-based approaches where applicableTranslate operational problems into solvable AI solutionsPrototype and validate solutions using real industrial datasetsDocument models clearly for engineering, operations, and regulatory reviewRequirements:Technical SkillsHands-on experience with machine learning for time-series dataHands on experience with LLMs and prompt engineeringExperience building or integrating agentic AI workflowsFamiliarity with RAG, vector databases, LangChain like frameworksSolid understanding of statistics, signal processing, and anomaly detectionExperience handling IoT data pipelines(streaming and batch)Familiarity with cloud platforms and containerization (Docker/Kubernetes)Domain & Systems AwarenessUnderstanding of industrial or physical systems (water, energy, manufacturing, or utilities preferred)