Senior AI Software Engineer

QXO•Kent, WA

About The Position

QXO is the largest publicly traded distributor of roofing, waterproofing, and complementary building products in the United States. The company aims to become the tech-enabled leader in the $800 billion building products distribution industry and generate outsized value for shareholders. QXO is targeting $50 billion in annual revenues within the next decade through accretive acquisitions and organic growth. QXO is hiring an AI Engineer to design, build, and operate production-grade AI agents that power pricing, quoting, and ecommerce-driven revenue workflows across our platforms. This is a hands-on engineering role focused on agentic systems, LLM orchestration, and real-world automation—not research prototypes. You’ll build intelligent agents that integrate with pricing engines, catalogs, CRM, and data platforms, with a direct impact on conversion, margin, and operational efficiency. You’ll work closely with product, engineering, and GTM partners to translate complex business workflows into reliable, observable, and scalable AI-powered systems.

Requirements

3–7+ years of experience as a Software Engineer, AI Engineer, or Machine Learning Engineer.
Proven experience building and operating LLM-driven or agentic applications in production.
Hands-on experience with agent frameworks or orchestration libraries (e.g., LangChain, LlamaIndex, AutoGen, Semantic Kernel, or similar).
Strong programming skills in Python (or TypeScript/Node).
Experience integrating LLMs with APIs, databases, vector stores, and retrieval systems.
Solid understanding of CI/CD, containerization (Docker), and cloud deployment (AWS, GCP, or Azure).
Experience testing, evaluating, and monitoring AI systems in real-world environments.
Comfort working in ambiguous, fast-moving environments with end-to-end ownership.

Nice To Haves

Experience building pricing, quoting, ecommerce, or monetization systems.
Familiarity with MCP servers or equivalent tool-integration architectures.
Experience with vector databases and search/retrieval systems.
Exposure to workflow engines, event-driven systems, or MLOps tooling.
Background in B2B, commerce, or operationally complex industries (e.g., construction, manufacturing, distribution).
Experience contributing to internal platforms or shared AI tooling.

Responsibilities

Build & Deploy AI Agents
Design and implement AI agents using modern orchestration frameworks (e.g., LangChain, LlamaIndex, OpenAI-based ecosystems, or equivalents).
Build tool-serving architectures (including MCP servers or equivalent patterns) to enable secure, scalable agent capabilities.
Develop agentic workflows that perform multi-step reasoning and interact with structured and unstructured data.
Package, deploy, and operate agents in production with a focus on reliability, performance, and observability.
Revenue, Pricing & Ecommerce Use Cases
Build agents that support revenue-generating workflows such as:
Generating bills of materials (BOMs), estimates, and quotes from drawings, specs, takeoffs, or opportunity data
Pricing validation, margin checks, and versioned quoting
Enrichment and prioritization of leads or accounts for digital GTM channels
Integrate AI systems with pricing/catalog services, ecommerce platforms, CRM, and internal APIs.
Partner with the business to identify high-ROI automation opportunities and measure impact on conversion, pricing accuracy, speed to quote, and revenue metrics.
Engineering, Testing & Operations
Develop reusable libraries, patterns, and internal tooling for agent development.
Build CI/CD pipelines, automated tests, and evaluation harnesses for LLM-powered systems.
Monitor agent behavior in production, diagnose failures, and iterate quickly.
Implement logging, analytics, and feedback loops to continuously improve system performance and safety.
Collaboration & Standards
Work cross-functionally with product, engineering, and domain experts to design AI-powered workflows.
Participate in design and code reviews, contributing to shared engineering standards.
Help define best practices for AI evaluation, observability, and responsible deployment.

Benefits

Annual performance bonus
Long term incentive (equity/stock)
401(k) with employer match
Medical, dental, and vision insurance
PTO, company holidays, and parental leave
Paid Time Off/Paid Sick Leave: Applicants can expect to accrue 15 days of paid time off during their first year (4.62 hours for every 80 hours worked) and increased accruals after five years of service.
Paid training and certifications
Legal assistance and identity protection
Pet insurance
Employee assistance program (EAP)