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Serve as the primary technical contact during implementation: run discovery, capture operational and data requirements, translate needs into specs for offshore model development, manage technical customer communication, identify and resolve risks, and partner with delivery/product teams to accelerate time to value.

Lead end-to-end customer implementation projects: own project plans, coordinate Technical Consultants and offshore teams, run meetings, manage risks/escalations, track deliverables in PM tools, communicate status to stakeholders, and improve workflows while supporting multiple customers across time zones.

Implement, validate, and deploy ML and rule-based models for industrial clients. Perform tag mapping from P&IDs/PFDs and control systems, ensure model quality through validation and QA, collaborate with Project Managers and Technical Consultants, automate model-building tasks, and provide feedback to improve product and deployment processes.

Act as a trusted partner to industrial customers in Oman to drive adoption of Uptime AI's platform, translate insights into actionable reliability and efficiency improvements, manage stakeholders, deliver training, track business impact, and coordinate with internal teams to ensure measurable operational outcomes and ROI.

Lead end-to-end customer implementations of UptimeAI's platform: gather requirements, map tags from P&IDs/PFDs, deploy and validate ML or rule-based models in OT environments (DCS/SCADA/historians), coordinate global and offshore teams, manage timelines and scope, provide product feedback, and automate model-building workflows.

Lead business development to expand UptimeAI’s presence in APAC and the Middle East. Build and qualify pipeline, execute GTM strategies, engage enterprise clients, create sales enablement assets, align with sales and marketing, manage a BD team, and track performance to meet revenue targets.

Drive enterprise client acquisition in APAC and Middle East by building qualified pipeline, executing GTM strategies, engaging stakeholders, creating sales enablement content, aligning with sales and marketing, and tracking performance to meet revenue targets.

Design, build, and deploy machine learning models and data pipelines end-to-end; implement production services and APIs; collaborate with product and engineering to productionize analytics, monitor model performance, and ensure scalable full‑stack integration of data solutions.

Lead design, build, and deploy production-grade AI/ML systems for predictive maintenance and process optimization using hybrid first-principles and data-driven models. Handle high-frequency time-series sensor data, operationalize low-latency inference at the edge, collaborate with product/engineering/domain experts, drive model interpretability and scalability, mentor team members, and contribute thought leadership.