Senior AI Engineer

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Logo of The Home Depot

The Home Depot

10,000+ employees

Founded 1978

🛒 Retail

👥 B2C

💰 Debt Financing on 2007-07

Retail • B2C

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.

📋 Description

• responsible for designing, building, scaling, and optimizing production-grade Agentic AI systems • collaborating and pairing with other product team members (UX, engineering, and product management) • documenting, reviewing, and ensuring all quality and change control standards are met • writing custom code or scripts to automate infrastructure, monitoring services, and test cases • configuring commercial off the shelf solutions to align with evolving business needs • creating meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively • participating in learning activities around modern software design, machine learning, and development core practices • monitoring tools and participating in conversations to encourage collaboration across product teams

🎯 Requirements

• 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 AI/ML foundations, including transformers, embeddings, deep learning, prompt engineering, agentic reasoning patterns, and vector databases • experience developing orchestration layers (task execution, routing, planning, workflows) and seamlessly integrating AI solutions with enterprise platforms, APIs, and business systems • expertise in cloud-native architectures, containerization (Docker) and orchestration (Kubernetes/GKE), infrastructure as code (e.g., Terraform) • hands-on implementation of MLOps/LLMOps best practices (CI/CD, automated testing, model versioning and registries, governance, compliance, and security) • experience building automated CI/CD pipelines for AI/agentic systems, implementing progressive rollout strategies (canary, blue-green, and shadow deployments) with automated rollback • excellent cross-functional communication and collaboration skills

🏖️ Benefits

• health care benefits • 401K • ESPP • paid time off • success sharing bonus

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