The Home Depot
The Home Depot
The Home Depot is a large home improvement retailer serving homeowners, DIY customers, and professional contractors through physical stores and an online platform. Its offering spans building materials, home improvement supplies, lawn and garden products, and related services, supported by operations across retail, construction, and logistics. The company hires across a broad workforce and emphasizes customer service, associate engagement, and a diverse, inclusive workplace.

Staff Software Engineer, Cloud Platform Products – Remote

Lead the design and delivery of Google Cloud and GKE platform products that support agentic AI workloads at The Home Depot. Improve secure scalability, reliability, developer self-service, and engineering delivery practices.

Description

  • Own cloud platform products for agentic workloads from initial design through release and ongoing operations
  • Turn ambiguous initiatives into sequenced work that supports predictable, incremental, low-risk delivery
  • Resolve technical blockers, dependencies, and delivery bottlenecks
  • Create reusable services, libraries, templates, paved paths, and automation
  • Advance CI/CD, progressive delivery, infrastructure as code, GitOps, testing, and release practices
  • Promote AI-assisted development and agentic engineering workflows
  • Write production code for complex, high-risk, and critical-path initiatives
  • Monitor delivery health metrics and use them to drive improvements
  • Increase platform adoption through documentation, reference architectures, self-service workflows, and better developer experiences
  • Set the technical vision, architecture, and long-term direction for cloud platform products
  • Lead architecture reviews, design sessions, and technical deep dives
  • Assess emerging technologies across AI infrastructure, LLM gateways, agent runtimes, MCP and tool integration, model serving, and orchestration
  • Work with architecture, security, and reliability teams to satisfy enterprise standards
  • Establish SLOs, observability, alerting, runbooks, and on-call readiness
  • Act as the technical escalation point for complex production incidents and lead root cause analysis
  • Design systems for supportability, scalability, high availability, and cost efficiency
  • Develop engineers through coaching, design guidance, code reviews, and pairing
  • Strengthen engineering standards and delegate ownership to develop technical leaders
  • Build communities of practice around cloud-native development, agentic AI, and platform engineering

Requirements

  • Be at least eighteen years old
  • Have legal authorization to work in the United States
  • Demonstrate mastery of an object-oriented programming language, preferably Go
  • Bring extensive experience designing, building, and delivering distributed cloud-native systems
  • Have production experience with Google Cloud Platform and Kubernetes, including GKE
  • Have led architecture, technical decisions, and delivery across multiple applications or teams
  • Have at least seven years of professional experience
  • Hold a bachelor's degree or equivalent qualification in a related field
  • Preferred: Bring eight or more years of software engineering experience with technical leadership across large-scale platforms or distributed systems
  • Possess deep expertise in Go, Google Cloud, Kubernetes, infrastructure as code, GitOps, automation, CI/CD, progressive delivery, observability, cloud security, and platform engineering
  • Have built platforms for agentic AI workloads, including LLM gateways, agent runtimes, model serving, MCP integration, orchestration layers, and vector databases
  • Have designed developer platforms, APIs, and self-service experiences
  • Have partnered with SRE or reliability engineering teams to build highly available production systems
  • Have led enterprise architecture reviews and influenced technical direction across teams
  • Demonstrate the ability to align engineering, product, architecture, security, and operations stakeholders
  • Show a track record of mentoring engineers and advancing technical excellence across an organization
  • Have experience supporting highly available, 24/7 retail platforms
  • Google Cloud Professional certifications are a plus

Benefits

  • Remote or virtual work arrangement
  • Typically involves less than 10% overnight travel
  • Professional development through technical coaching, design guidance, code reviews, pairing, continuous learning, and hands-on experimentation
  • Opportunity to work with emerging AI infrastructure, agentic AI, and cloud platform technologies

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