As an AI Technical Program Manager, you will manage large-scale cross-functional programs, driving solutions for AI delivery, ensuring system performance, and engaging with product and engineering teams.

Lead the design and implementation of secure authentication, authorization, and master data management systems for logistics. Optimize algorithms and scale databases in cloud environments while mentoring engineering teams and ensuring best practices.

Lead transformation of global support by building AI-human hybrid workflows, drive AI-powered triage/resolution, own CSAT/NPS/SLA metrics, translate support insights into product priorities, and upskill the team into AI trainers, knowledge architects, and escalation specialists.

Lead design and implementation of scalable backend systems and production AI agents across an event-driven microservices platform. Architect services, integrate LLM-powered agents, ensure reliability and test coverage, mentor engineers, perform root-cause analysis, and collaborate with DevOps and frontend teams to deploy and maintain high-throughput supply-chain systems.

Lead development of AI-native data products and BI portfolio that power dashboards, AI agents, and automated workflows. Own product P&L, validate hypotheses via SQL/Python, define data models, ship prototypes, and coordinate across AI teams while managing BI execution and mentoring a direct report.

Lead the development of predictive modeling and supply chain analytics, focusing on ETA prediction for transportation logistics using advanced analytics and machine learning techniques.

Design, develop, test, and maintain backend services and data models for a high-scale logistics platform. Build microservices and REST APIs, integrate with front-end, deploy to cloud (AWS/Azure), ensure high test coverage and production reliability, and mentor engineers while contributing to AI initiatives and system architecture.

Lead the design and development of complex backend systems, focusing on architecture and implementation while mentoring engineers and integrating AI solutions.

Lead analytics for Growth & Retention and Customer 360: build analytics data models, dashboards, predictive churn and propensity models, apply LLM/ML techniques for automated insights, and partner with cross-functional stakeholders to operationalize KPIs.