Senior AI Engineer

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. Our critical communications, video security and command center technologies support public safety agencies and enterprises alike, enabling the coordination that's critical for safer communities, safer schools, safer hospitals and safer businesses. Connect with a career that matters, and help us build a safer future.

The Supply Chain AI Transformation department at Motorola Solutions manages projects and sets goals, transforming solutions for the future. Enable data-driven supply chain decision-making through AI-powered analytics, enterprise reporting, and scalable data infrastructure.

The Senior AI Engineer will play a critical role in designing and deploying autonomous AI agents that enable multi-step reasoning, complex analysis, and optimization of supply chain processes. This position will lead the expansion of AI initiatives across the supply chain organization, with a particular focus on automation solutions that drive operational efficiency and data-driven decision-making.

As a key member of the AI+BI team, you will work at the intersection of artificial intelligence, data engineering, and supply chain operations to create innovative solutions that transform how business users interact with data and automate complex supply chain processes.

• Design and Develop Autonomous AI Agents:
  Design, develop, and deploy autonomous AI agents capable of multi-step reasoning, planning, and tool use to execute complex supply chain tasks, including data analysis and process automation.
• Develop ChatGPT for Data Experiences:
  Optimize conversational AI interfaces that enable natural language querying of supply chain data, including prompt engineering, data integration, and performance optimization.
• Execute AI Projects Across Supply Chain:
  Lead and execute AI initiatives across supply chain domains (procurement, logistics, inventory, forecasting, automation, etc.), from conception through deployment.
• Develop and Execute Solutions:
  As a senior engineer, take ownership of end-to-end solution development including architecture design, implementation, testing, and deployment of AI-powered supply chain solutions.
• Automation Development:
  Identify, design, and implement AI-driven automation solutions that optimize supply chain processes and drive operational efficiency.
• Data Integration:
  Build seamless connections between AI systems and underlying data infrastructure (data warehouses, APIs, databases, BI tools).
• Stakeholder
  
  Collaboration:
  
  Work closely with supply chain business leaders and cross-functional teams to understand requirements, deliver value-driven solutions, and ensure successful adoption.
• Technical Leadership:
  Provide technical guidance, establish AI development best practices, and mentor junior engineers.
• Continuous Improvement:
  Stay current with AI/LLM advancements, evaluate new technologies, and continuously optimize existing solutions for performance and cost-effectiveness.
• Documentation & Knowledge Sharing:
  Create comprehensive technical documentation and share knowledge across the organization.

• Proven track record of developing and deploying production AI/ML solutions.
• Experience working with supply chain, logistics, or operations data (preferred).

AI/ML Expertise:

• Deep understanding of LLM architectures (GPT, Claude, Llama, etc.) and their applications.
• Strong experience with agent design, tool-use, and multi-step reasoning frameworks.
• Experience with prompt engineering and conversational AI systems.
• Proficiency in fine-tuning and optimizing LLM models.
• Experience with AI/ML frameworks (Lang Chain, Llama Index, Hugging Face, Tensor Flow, PyTorch).
• Knowledge of model evaluation, testing, and performance optimization.

Programming & Development:

• Strong proficiency in Python (required).
• Experience with API development (REST, Graph
  
  QL).
• Familiarity with cloud platforms (Azure, AWS, or GCP).
• Experience with version control (Git) and CI/CD practices.
• Knowledge of software engineering best practices and design patterns.

Data & Integration:

• Understanding of data engineering concepts (ETL/ELT, data pipelines).
• Experience integrating AI systems with databases, data warehouses, and APIs.
• Familiarity with SQL and data querying.
• Knowledge of data security and governance practices.

Tools & Technologies:

• Experience with ChatGPT API, OpenAI, or similar LLM platforms.
• Knowledge of containerization (Docker, Kubernetes).
• Experience with monitoring and observability tools.

• Advanced degree (Master's or PhD) in AI/ML, Computer Science, or related field.
• Experience in supply chain, logistics, or manufacturing industries.
• Experience with AWS Bedrock, Azure OpenAI, or Google Vertex AI.
• Knowledge of MLOps practices and model deployment pipelines.
• Experience with BI tools (Power…