Senior AI Engineer

Beacon Roofing Supply, Inc; Seattle (WA); On-site; USD 150,000 - 220,000; Full time

Benefits offered by this job

Annual performance bonus

401(k) with employer match

Medical, dental, and vision insurance

Paid Time Off

Job summary

A leading distributor in building products is looking for a Senior Software Engineer AI to design and build AI agents that optimize workflows. The candidate should have experience with frameworks like LangChain and OpenAI/MCP, alongside strong skills in Python and machine learning. The role includes responsibilities such as architecting AI agents and monitoring their performance in production. A competitive salary of $150,000 - $220,000 is offered along with various benefits including performance bonuses and PTO.

Qualifications

• 3–7+ years of experience as a Software Engineer, Machine Learning Engineer, or AI Engineer.
• Proven experience building AI agents or LLM-driven applications in production contexts.
• Hands-on with libraries/frameworks such as LangChain and OpenAI/MCP.

Responsibilities

• Architect and build AI agents using modern agent frameworks.
• Implement custom tools and integrations for agent capabilities.
• Monitor agent performance and iterate quickly on improvements.

Skills

Python

Machine Learning

AI Engineering

Problem-solving

Collaboration

Tools

LangChain

OpenAI/MCP

Docker

AWS

Job description

We’re looking for bold, entrepreneurial talent ready to help build something extraordinary — and reshape the future of building products distribution.

QXO is a publicly traded company founded by Brad Jacobs with the goal of building the market‑leading company in the building products distribution industry. On April 30, 2025, QXO completed its first acquisition: Beacon Building Products, a leading distributor in the sector.

We are building a customer‑focused, tech‑enabled, and innovation‑driven business that will scale rapidly through accretive M&A, organic growth, and greenfield expansion. Our strategy is rooted in delivering exceptional customer experiences, improving operational efficiency, and leveraging data, digital tools, and AI to modernize a historically under‑digitized industry.

What you’ll do:

We are seeking a highly skilled Senior Software Eng AI to design, build, and deploy production‑grade AI agents that augment workflows across our organization. The ideal candidate has hands‑on experience with agentic frameworks, MCP servers, LLM orchestration libraries, and robust testing/monitoring practices. This role blends software engineering excellence with applied machine learning and offers the opportunity to push the boundaries of intelligent automation in real business environments.

Responsibilities

• Architect, build, and optimize AI agents using modern agent frameworks (e.g., LangChain, LlamaIndex, OpenAI/MCP‑based ecosystems, or equivalents).
• Implement MCP (Model Context Protocol) servers, custom tools, and integrations to enable secure and scalable agent capabilities.
• Design agentic workflows that can operate autonomously, perform multi‑step reasoning, and interact with structured/unstructured data sources.
• Package and deploy agents into production environments with attention to reliability, observability, and performance.

Sales & Marketing Agent Use Cases

• Build agents that support Sales Representatives, such as lead and account research, enrichment, and prioritization.
• Drafting and personalizing outbound emails and sequences.
• Summarizing calls, meetings, and account activity to drive next‑best actions.
• Integrating with CRM and sales tools (e.g., Salesforce, HubSpot, Outreach) to automate data entry and insight surfacing.
• Generating detailed bills of materials (BOMs), estimates, and quotes from drawings, specs, takeoffs, or CRM/opportunity data, including price checks, margin validation, and versioning.
• Build agents that support Marketing, such as generating and localizing content for campaigns, landing pages, and nurture programs.
• Assisting with audience segmentation, experimentation, and performance analysis.
• Powering internal “marketing copilots” that answer questions from campaign, web, and analytics data.
• Partner with the business to identify high‑ROI workflows for automation and to measure the impact of deployed agents on pipeline, conversion, quoting speed/accuracy, and engagement metrics.

Systems Engineering & Tooling

• Develop internal libraries, reusable modules, and standardized patterns for building agentic applications.
• Integrate agent systems with enterprise APIs, cloud services, databases, pricing/catalog systems, and operational infrastructure.
• Build CI/CD pipelines for both model‑related code and agent‑specific behavior, including automated testing, evaluation harnesses, and regression detection for LLM‑powered systems.

Testing, Evaluation & Monitoring

• Create frameworks for continuous evaluation of agents, including prompt tests, scenario simulations, and safety/robustness checks.
• Monitor agent performance in production, diagnose failures, and iterate quickly on improvements.
• Implement logging, analytics, and feedback loops to guide ongoing training or refinement—especially for critical revenue and quoting workflows.

Collaboration & Strategy

• Work closely with product, engineering, Sales, Marketing, and domain experts to translate business processes into agentic flows.
• Partner with stakeholders to identify automation opportunities and design AI‑powered operational solutions.
• Contribute to internal documentation, best practices, and AI engineering guidelines.

What you’ll bring:

Required

• 3–7+ years of experience as a Software Engineer, Machine Learning Engineer, or AI Engineer (flexible based on seniority).
• Proven experience building AI agents or LLM‑driven applications in production contexts.
• Hands‑on work with libraries/frameworks such as LangChain, OpenAI/MCP, LlamaIndex, or similar orchestration tools.
• Proficiency with Python (or Typescript/Node) and modern development workflows.
• Experience integrating LLMs with external tools, APIs, vector databases, and retrieval systems.
• Strong understanding of CI/CD, containerization (Docker), cloud deployment (AWS/GCP/Azure), and DevOps fundamentals.
• Familiarity with automated testing approaches for LLM applications (unit tests, scenario testing, eval harnesses).
• Excellent problem‑solving skills and the ability to design resilient systems in ambiguous environments.

Preferred

• Experience deploying and scaling MCP servers, custom toolchains, or enterprise agent frameworks.
• Prior work building tools or automations for Sales, Marketing, or RevOps teams (e.g., CRM‑integrated apps, quoting tools, outbound tooling, marketing analytics or experimentation platforms).
• Background or project experience in the building industry (construction, materials distribution, building automation, supply chain, procurement) or other B2B industry.
• Experience with workflow engines (Airflow, Prefect, etc.) and/or MLOps (Mlflow, Flyte, etc.) and event‑driven architectures.
• Familiarity with vector and search/retrieval systems.
• Understanding of prompt engineering, model fine‑tuning, or RLHF‑style evaluation frameworks.

What you’ll earn

• Base pay range: $150,000 - $220,000
• 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)

QXO is an Equal Opportunity Employer. We value diversity and do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, or any other protected status.

To comply with Pay Transparency laws, employers must disclose an annual salary range. Actual offers depend on factors such as location, experience, skills, and market data. This position may also offer variable compensation.

Please contact [e-mail] if you have any questions related to this job posting.