Applied AI Engineer I – Supply Chain

Company Overview

At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.

Department Overview

The Supply Chain AI & Data team drives the strategic transformation of our operations in alignment with Vision 2030. We are building the next evolution of data on AI—moving beyond traditional analytics to architect an intelligent, autonomous supply chain ecosystem. As the strategic engine behind critical initiatives, our mission is to fundamentally redefine how the business operates, turning complex logistical challenges into proactive, resilient, and forward-looking capabilities.

Job Description

About the Role

As an Applied AI Engineer I on our Supply Chain team, you will help bridge the gap between cutting-edge artificial intelligence and real-world logistical challenges. You will work closely with senior engineers, data scientists, and supply chain operators to build and deploy intelligent systems that optimize our operations. A major focus of this role will be developing Conversational AI interfaces for our supply chain data, and subsequently evolving those tools into proactive alerting systems and semi/fully autonomous AI agents that can execute decisions in real time. Moving from foundational support to owning specific project components, you will play a hands-on role in making our supply chain smarter, faster, and more resilient.

Key Responsibilities

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Conversational AI for Data: Build and maintain Large Language Model (LLM) applications (such as Text-to-SQL or RAG systems) that allow stakeholders to easily query ERP, warehouse, and logistics data using natural language.

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Proactive Alerting Systems: Expand conversational tools into active monitoring systems that continuously analyze supply chain data streams, detect anomalies (e.g., inventory shortages, shipping delays), and automatically push alerts and actionable recommendations to operators before bottlenecks occur.

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Autonomous & Semi-Autonomous Agents: Develop and deploy agentic AI workflows that can take independent action—such as rerouting shipments, generating purchase orders, or automating vendor communications—while designing secure Human-in-the-Loop (HITL) fallback mechanisms.

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Model Development & Deployment: Collaborate on designing, training, and deploying standard machine learning models for supply chain optimization (e.g., route planning, demand forecasting).

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Data Pipeline Engineering: Write clean, production-ready code to extract, clean, and preprocess large datasets from our core operational systems to feed both predictive models...