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.