
10,000+ employees
Founded 1978
🏗️ Construction
📦 Logistics
đź›’ Retail
đź’° Debt Financing on 2007-07
Construction • Logistics • Retail
The Home Depot is a leading home improvement retailer, offering a wide range of building materials, home improvement products, lawn and garden products, and related services. The company operates both physical stores and an online platform, providing comprehensive solutions for DIY enthusiasts, professional contractors, and homeowners. The Home Depot is committed to diversity, equity, and inclusion, providing employment opportunities and benefits to a diverse workforce. Additionally, the company places a high emphasis on customer service and associate engagement to maintain its position as a trusted leader in the home improvement industry.
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10,000+ employees
Founded 1978
🏗️ Construction
📦 Logistics
đź›’ Retail
đź’° Debt Financing on 2007-07
Construction • Logistics • Retail
The Home Depot is a leading home improvement retailer, offering a wide range of building materials, home improvement products, lawn and garden products, and related services. The company operates both physical stores and an online platform, providing comprehensive solutions for DIY enthusiasts, professional contractors, and homeowners. The Home Depot is committed to diversity, equity, and inclusion, providing employment opportunities and benefits to a diverse workforce. Additionally, the company places a high emphasis on customer service and associate engagement to maintain its position as a trusted leader in the home improvement industry.
• Design, build, scale, and optimize production-grade Agentic AI systems that drive business outcomes across The Home Depot • Develop scalable applications powered by LLMs, SLMs, RAG frameworks, and autonomous agents • Build orchestration layers for multi-agent workflows, tool integration, and planning • Develop infrastructure for reliable, large-scale cloud deployment • Partner with product, engineering, and business teams to prototype solutions and transition AI capabilities from concept to production • Collaborate with UX, engineering, and product management to create secure, reliable, scalable machine learning solutions • Document, review, and ensure quality and change control standards are met • Work with product teams to ensure developer-ready, understandable, and testable user stories • Write custom code and scripts to automate infrastructure, monitoring services, test cases, and destructive testing • Configure commercial off-the-shelf solutions for evolving business needs • Create dashboards, logging, alerting, and responses to proactively address issues • Answer questions from product and support teams and encourage collaboration across product teams • Provide application support for production software • Monitor production Service Level Objectives and review performance and capacity across code, infrastructure, data, message processing, and prediction quality
• 6+ years of experience in AI, Machine Learning Engineering, or Software Engineering • Strong Python development skills and modern software engineering practices • Proven experience building and deploying production-grade AI solutions using LLMs, SLMs, RAG frameworks, copilots, agents, and multi-agent systems • Deep understanding of transformers, embeddings, deep learning, prompt engineering, agentic reasoning patterns, and vector databases • Experience developing orchestration layers for task execution, routing, planning, and workflows • Experience integrating AI solutions with enterprise platforms, APIs, and business systems • Expertise in cloud-native architectures, Docker, Kubernetes/GKE, Terraform, AI pipeline design, MLOps/LLMOps, CI/CD, automated testing, model versioning and registries, governance, compliance, and security • Experience with progressive rollout strategies, automated rollback, observability, logging, metrics, distributed tracing, and automated alerting • Ability to optimize AI systems for performance, reliability, scalability, latency, cost efficiency, and token use, and debug operational failure modes • Excellent cross-functional communication and collaboration skills • Must be eighteen years of age or older • Must be legally permitted to work in the United States • Preferred: Vertex AI, Gemini, Google ADK, LangGraph, CrewAI, AutoGen, Kubernetes/GKE, GPU/accelerator provisioning and autoscaling, model registries, feature stores, vector databases, Node.js, React, REST, API design, Linux, Git, modern deployment toolchains • Preferred background in retail, supply chain, manufacturing, eCommerce, logistics, or finance • Preferred knowledge of Responsible AI, evaluation frameworks, reliability engineering, AI governance guardrails, mentoring, and AI engineering standards • Minimum education: high school diploma and/or GED
• Health care benefits • 401K • ESPP • Paid time off • Success sharing bonus
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