Senior AI Engineer

GXO Logistics, Inc.; High Point (NC); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Full health insurance (medical, dental, and vision)

401(k)

Life insurance

Disability

Company incentive plan

Job summary

A logistics technology company based in North Carolina is seeking an AI Engineer specializing in Generative AI products. The role involves designing, developing, and deploying AI-powered applications to enhance supply chain operations. Candidates should have 3–5 years in AI/ML engineering with strong software development skills. The company offers competitive compensation, including full health insurance, 401(k), and other generous perks.

Qualifications

• 3–5 years of experience in software engineering, AI/ML engineering, or data science.
• At least 1 year focused on agentic AI development.
• Hands-on experience with AI agent development frameworks.

Responsibilities

• Design, develop, deploy, and maintain AI agents and software for supply chain operations.
• Apply prompt engineering and optimize LLM integrations.
• Collaborate with stakeholders to understand use cases.

Skills

Software engineering

AI/ML engineering

Data science

Cloud environments (GCP)

Problem-solving skills

Education

Advanced degree in a relevant field

Tools

Python

SQL

Flask

FastAPI

Docker

Kubernetes

Job description

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.