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Senior AI Engineer, Platform
QXO
40 minutes ago
Full-time
On-site
Washington, District of Columbia, United States
What You'll Build On
Data: transaction, pricing, customer, and operational data from the largest publicly traded distributor of roofing and waterproofing products in the United States, including the businesses it acquires. Users: sales, operations, finance, and executive teams across QXO.
The Role The
Senior AI Engineer,
Platform owns the AI services that make QXO's data and AI platform dependable at enterprise scale: how agents find and use business data, how answers stay grounded in trusted definitions, how access controls hold across every AI workflow, and how quality is measured and improved over time. The core challenge is balance. Answer quality, reliability, response time, cost, and secure access compete with one another, and this role makes those trade-offs in production. It owns the AI services and runtime, and works closely with the engineers who lead the application and user experience.
The Impact You'll Have Make the platform's AI services reliable, fast, and cost-effective as usage grows across the business. Ground AI responses in trusted business data and approved metric definitions, so answers match the figures the business already reports. Continuously measure and improve AI quality, catching regressions before they reach users. Ensure access controls hold consistently across every AI workflow. Give engineering teams across QXO a dependable foundation for building their own AI agents
What you'll bring 5+ years backend engineering experience building and operating production software. Production experience building agentic workflows on large language models, including agents, retrieval systems, and tool-calling workflows, using frameworks such as LangChain and LangGraph. Experience with online and offline evaluation of agentic solutions, including building test sets, automated grading, quality monitoring, and acting on the results. Strong Python, including production services used by other engineering teams. Ownership of production systems, including deployment, monitoring, and on-call support. Working knowledge of access control and the handling of sensitive data. Demonstrated, effective use of AI-assisted development tools, with accountability for the quality of their output. A degree in computer science or a related field, or equivalent practical experience.
Nice to Have Experience developing guardrails for agentic workflows, including controls for safe tool use, data access, and reliable behavior. Experience optimizing the cost and response time of applications built on large language models. Experience with a cloud data warehouse and shared metric definitions. Background in distribution, supply chain, or another B2B business.
Data: transaction, pricing, customer, and operational data from the largest publicly traded distributor of roofing and waterproofing products in the United States, including the businesses it acquires. Users: sales, operations, finance, and executive teams across QXO.
The Role The
Senior AI Engineer,
Platform owns the AI services that make QXO's data and AI platform dependable at enterprise scale: how agents find and use business data, how answers stay grounded in trusted definitions, how access controls hold across every AI workflow, and how quality is measured and improved over time. The core challenge is balance. Answer quality, reliability, response time, cost, and secure access compete with one another, and this role makes those trade-offs in production. It owns the AI services and runtime, and works closely with the engineers who lead the application and user experience.
The Impact You'll Have Make the platform's AI services reliable, fast, and cost-effective as usage grows across the business. Ground AI responses in trusted business data and approved metric definitions, so answers match the figures the business already reports. Continuously measure and improve AI quality, catching regressions before they reach users. Ensure access controls hold consistently across every AI workflow. Give engineering teams across QXO a dependable foundation for building their own AI agents
What you'll bring 5+ years backend engineering experience building and operating production software. Production experience building agentic workflows on large language models, including agents, retrieval systems, and tool-calling workflows, using frameworks such as LangChain and LangGraph. Experience with online and offline evaluation of agentic solutions, including building test sets, automated grading, quality monitoring, and acting on the results. Strong Python, including production services used by other engineering teams. Ownership of production systems, including deployment, monitoring, and on-call support. Working knowledge of access control and the handling of sensitive data. Demonstrated, effective use of AI-assisted development tools, with accountability for the quality of their output. A degree in computer science or a related field, or equivalent practical experience.
Nice to Have Experience developing guardrails for agentic workflows, including controls for safe tool use, data access, and reliable behavior. Experience optimizing the cost and response time of applications built on large language models. Experience with a cloud data warehouse and shared metric definitions. Background in distribution, supply chain, or another B2B business.