Staff Software Engineer – Cloud Platform Products

The Home Depot

. Own technical delivery of cloud platform products supporting agentic workloads from design through release and ongoing operation .

Posted 10/7/2026full-timeRemote • United StatesLead💰 $120,000 - $190,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and delivering cloud-native systems, with a strong focus on automation, CI/CD, and observability. Proven ability to lead technical initiatives, mentor engineers, and drive improvements in developer experience and platform engineering.

Highest-signal resume keywords

Golang ProgrammingGoogle Cloud PlatformKubernetes (GKE)CI/CD AutomationCloud-Native Architecture

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Object-Oriented ProgrammingDistributed Systems DesignIaC (Infrastructure as Code)GitOpsObservabilityCloud SecurityPlatform EngineeringAI WorkloadsAPIs DesignSelf-Service Experiences

Soft Skills

Technical LeadershipMentoringCollaborationProblem-SolvingCommunication

Tools & Technologies

Google CloudKubernetesMCP IntegrationOrchestration LayersVector Databases

Certifications & Qualifications

Google Cloud Professional Certifications

Industry Keywords

Cloud-Native DevelopmentAgentic AISRE (Site Reliability Engineering)High Availability Systems24x7 Retail Platforms

Tech Stack

Tools & technologies

CloudDistributed SystemsGoogle Cloud PlatformKubernetesGo

About the role

Key responsibilities & impact

Own technical delivery of cloud platform products supporting agentic workloads from design through release and ongoing operation
Break ambiguous initiatives into sequenced, executable work and maintain predictable, incremental, low-risk delivery
Identify and remove technical blockers, dependencies, and bottlenecks
Build reusable services, libraries, templates, paved paths, and automation
Establish and improve CI/CD, progressive delivery, IaC/GitOps, testing, and release practices
Champion AI-assisted development and agentic workflows
Contribute hands-on code to complex, high-risk, and critical-path work
Track delivery health metrics and drive improvements
Drive adoption through documentation, reference architectures, self-service workflows, and developer experience improvements
Define technical vision, architecture, and long-term evolution of cloud platform products
Lead design and architecture reviews and technical deep dives
Evaluate and adopt emerging technologies in AI infrastructure, LLM gateways, agent runtimes, MCP/tool integration, model serving, and orchestration
Partner with architecture, security, and reliability teams to meet enterprise standards
Define SLOs, observability, alerting, runbooks, and on-call readiness
Serve as technical escalation point for complex production incidents and lead root cause analysis
Design for supportability, scalability, high availability, and cost efficiency
Mentor and develop engineers through coaching, design guidance, code reviews, and pairing
Raise engineering standards and delegate technical ownership to grow technical leaders
Foster communities of practice in cloud-native development, agentic AI, and platform engineering

Requirements

What you’ll need

Must be eighteen years of age or older
Must be legally permitted to work in the United States
Mastery of an object-oriented programming language, preferably Go
Extensive experience designing, building, and delivering distributed cloud-native systems
Proficiency with Google Cloud Platform and Kubernetes (GKE) in a production environment
Experience leading architecture, technical decisions, and delivery across multiple applications or teams
Minimum 7 years of work experience
Bachelor's degree or equivalent in a related field
Preferred: 8+ years of software engineering experience with demonstrated technical leadership across large-scale platforms or distributed systems
Deep expertise in Golang, Google Cloud, Kubernetes, IaC, GitOps, automation, CI/CD, progressive delivery, observability, cloud security, and platform engineering
Experience building platforms for agentic AI workloads, including LLM gateways, agent runtimes, model serving, MCP integration, orchestration layers, and vector databases
Experience designing developer platforms, APIs, and self-service experiences
Experience partnering with SRE/Reliability Engineering to build highly available production systems
Experience leading enterprise architecture reviews and influencing technical direction across teams
Demonstrated ability to align engineering, product, architecture, security, and operations stakeholders
Proven ability to mentor engineers and raise technical excellence across an organization
Experience supporting highly available 24x7 retail platforms
Google Cloud Professional certifications are a plus

Benefits

Comp & perks

Remote/Virtual work arrangement
Typically requires overnight travel less than 10% of the time
Professional development through technical coaching, design guidance, code reviews, pairing, continuous learning, and hands-on experimentation
Opportunity to work with emerging technologies in AI infrastructure, agentic AI, and cloud platforms