Senior AI Engineer

The Home Depot, a leader in retail and home improvement, is seeking a Senior AI Engineer to design, build, and scale production-grade agentic AI systems that drive measurable business outcomes. This role collaborates across data science, ML engineering, and software teams to turn AI concepts into enterprise-ready products, with a focus on LLM and SLM powered applications, RAG frameworks, and multi-agent workflows deployed in the cloud. The position is based in Denver, CO with a remote work option.

Responsibilities

• Delivery and Execution: Collaborate with UX, engineering, and product management to create secure, reliable, and scalable ML solutions; document and ensure quality and change-control standards are met; ensure user stories are developer-ready, easy to understand, and testable; write custom code to automate infrastructure, monitoring services, and test cases.
• Learning: Engage in ongoing learning around modern software design, machine learning, and development practices; proactively study articles, tutorials, and videos to stay current on technologies used across organizations.
• Support and Enablement: Field questions from product and support teams; monitor tools and foster cross-team collaboration; provide production application support; monitor production service level objectives and review the performance and capacity of code, infrastructure, data, messaging, and prediction quality.

Requirements

• Experience: 6+ years in AI, machine learning engineering, or software engineering with strong Python development skills and modern software engineering practices.
• AI Delivery: Proven experience building and deploying production-grade AI solutions using LLMs, SLMs, RAG frameworks, copilots, agents, and multi-agent systems.
• AI Foundations: Deep understanding of AI and ML fundamentals including transformers, embeddings, deep learning, prompt engineering, agentic reasoning patterns, and vector databases.
• Orchestration & Integration: Experience developing orchestration layers (task execution, routing, planning, workflows) and integrating AI solutions with enterprise platforms, APIs, and business systems.
• Infrastructure & MLOps: Expertise in cloud-native architectures, containerization (Docker) and orchestration (Kubernetes/GKE), infrastructure as code (Terraform), and AI pipeline design with hands-on MLOps/LLMOps practices (CI/CD, automated testing, model versioning and registries, governance, security) across the full AI/agent lifecycle.
• AIOps & Deployment Reliability: Experience building automated CI/CD pipelines for AI/agentic systems, progressive rollout strategies (canary, blue-green, shadow deployments) with automated rollback, and end-to-end observability (logs, metrics, distributed tracing, alerting) across models, agents, and orchestration layers to ensure reliability, performance, and cost/token efficiency at scale.
• Optimization & Debugging: Ability to optimize complex AI systems for performance, reliability, scalability, latency, cost efficiency, and token usage; adept at debugging operational failure modes.
• Execution & Collaboration: Excellent cross-functional communication and collaboration skills, with a proven track record of taking AI solutions from concept to production in complex enterprise environments.

Technologies

• Python, LLMs, SLMs, RAG frameworks
• Vertex AI, Gemini, Google ADK, LangGraph, CrewAI, AutoGen
• Node.js, React, REST, Linux, Git, Docker, Kubernetes, GKE
• Terraform, Transformers, Embeddings, Vector databases

Benefits

• Health care benefits
• 401K
• ESPP
• Paid time off
• Success sharing bonus

Direct Manager / Reports

• This position typically reports to a Software Engineer Manager or Senior Software Engineer Manager
• This position has 0 direct reports

Travel Requirements

Typically requires overnight travel 5% to 20% of the time.

Physical Requirements

• Most of the time spent sitting in a comfortable position with frequent movement opportunities
• Occasional light lifting may be required

Working Conditions

Located in a comfortable indoor environment. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications

• Must be eighteen years of age or older
• Must be legally permitted to work in the United States

Minimum Education

The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.

Preferred Education

No additional education

Minimum Years of Work Experience

2

Preferred Years of Work Experience

No additional years of experience

Certifications

None

Competencies

• Global Perspective
• Manages Ambiguity
• Nimble Learning
• Self-Development
• Collaborates
• Cultivates Innovation
• Situational Adaptability
• Communicates Effectively
• Drives Results
• Interpersonal Savvy