Role overview
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 will do::
We are seeking a highly skilled Senior Software Engineer, 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.
- 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.
- 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.
- 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.
- 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.
- 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 qualifications
- 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.
- 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)