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Senior AI Engineer
GXO Logistics, Inc.
1 hour ago
Full-time
On-site
High Point, North Carolina, United States
We’re out to transform transportation logistics through technology, and our multimillion-dollar commitment to IT underscores its importance to our vision. As an AI Engineer specializing in Generative AI products, you will design, develop, and deploy GenAI-powered applications that enhance supply chain operations. You will work at the intersection of AI research and engineering, transforming large language models and multimodal systems into scalable, production-ready tools that drive automation, decision-making, and customer experience across GXO’s logistics network.
Pay, benefits and more.
We are eager to attract the best, so we offer competitive compensation and a generous benefits package, including full health insurance (medical, dental and vision), 401(k), life insurance, disability and the opportunity to participate in a company incentive plan.
What you’ll do on a typical day
Design, develop, deploy, and maintain AI agents and software that enhance and support supply chain operations and technology. Apply prompt engineering, Retrieval-Augmented Generation (RAG), LLMorchestrationframeworks, MCP/function calling, evaluation techniques, and guardrails to optimize LLM integrations and build AI agents tailored to enterprise use cases. Ensure software engineering, DevOps, and cybersecurity best practices in development and deployment, including CI/CD pipelines, source control, and secure coding standards. Design and build, or collaborate with data engineering teams to develop ,
data models and pipelines that support and feed AI solutions, ensuring scalability, reliability, and data quality. Develop AI agent software and integrations using Python, SQL, and frameworks such as Flask and FastAPI. Build agile and portable AI solutions using containerization tools like Docker and Kubernetes. Collaborate with business and product stakeholders to understand use cases and educate teams on AI capabilities. Work closely with IT teams (infrastructure, InfoSec, data engineering) to define internal requirements and ensure seamless integration. Communicate effectively with leadership to secure resources, address issues, and provide project updates. Take ownership of projects end-to-end with minimal supervision. Mentor junior engineers on best practices in AI and software development through pair programming, code reviews, and architectural guidance. Stay current on emerging AI technologies and trends and contribute to the organization’s AI roadmap. At a minimum, you’ll need
3–5 years of experience in software engineering, AI/ML engineering, or data science, with at least 1 year focused on agentic AI development. Hands-on experience with AI agent development frameworks (e.g., Google’s Agent Development Kit, OpenAI Agents SDK). Knowledge of MCP and A2A protocols. Strong proficiency in cloud environments (GCP preferred; AWS and Azure acceptable). Experience in monitoring, troubleshooting, and optimizing deployed solutions. Strong analytical and problem-solving skills. It’d be great if you also had
Advanced degree in a relevant field. Experience in advanced AI techniques, such as fine-tuning LLMs or developing custom AI algorithms. Familiarity with logistics systems (e.g., WMS). Experience with Snowflake and its ecosystem. Hands-on experience with GCP Vertex AI Agent Builder.
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Design, develop, deploy, and maintain AI agents and software that enhance and support supply chain operations and technology. Apply prompt engineering, Retrieval-Augmented Generation (RAG), LLMorchestrationframeworks, MCP/function calling, evaluation techniques, and guardrails to optimize LLM integrations and build AI agents tailored to enterprise use cases. Ensure software engineering, DevOps, and cybersecurity best practices in development and deployment, including CI/CD pipelines, source control, and secure coding standards. Design and build, or collaborate with data engineering teams to develop ,
data models and pipelines that support and feed AI solutions, ensuring scalability, reliability, and data quality. Develop AI agent software and integrations using Python, SQL, and frameworks such as Flask and FastAPI. Build agile and portable AI solutions using containerization tools like Docker and Kubernetes. Collaborate with business and product stakeholders to understand use cases and educate teams on AI capabilities. Work closely with IT teams (infrastructure, InfoSec, data engineering) to define internal requirements and ensure seamless integration. Communicate effectively with leadership to secure resources, address issues, and provide project updates. Take ownership of projects end-to-end with minimal supervision. Mentor junior engineers on best practices in AI and software development through pair programming, code reviews, and architectural guidance. Stay current on emerging AI technologies and trends and contribute to the organization’s AI roadmap. At a minimum, you’ll need
3–5 years of experience in software engineering, AI/ML engineering, or data science, with at least 1 year focused on agentic AI development. Hands-on experience with AI agent development frameworks (e.g., Google’s Agent Development Kit, OpenAI Agents SDK). Knowledge of MCP and A2A protocols. Strong proficiency in cloud environments (GCP preferred; AWS and Azure acceptable). Experience in monitoring, troubleshooting, and optimizing deployed solutions. Strong analytical and problem-solving skills. It’d be great if you also had
Advanced degree in a relevant field. Experience in advanced AI techniques, such as fine-tuning LLMs or developing custom AI algorithms. Familiarity with logistics systems (e.g., WMS). Experience with Snowflake and its ecosystem. Hands-on experience with GCP Vertex AI Agent Builder.
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