Staff Software Engineer – Cloud Platform Products

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the technical delivery for cloud platform products that support agentic workloads, from the design phase to release and ongoing operation.

• Decompose ambiguous projects into organized, actionable tasks while ensuring consistent, incremental, and low-risk delivery.

• Identify and eliminate technical obstacles, dependencies, and bottlenecks.

• Develop reusable services, libraries, templates, paved paths, and automation tools.

• Establish and enhance CI/CD, progressive delivery, Infrastructure as Code (IaC)/GitOps, testing, and release practices.

• Advocate for AI-assisted development and agentic workflows.

• Actively contribute code to complex, high-stakes, and critical-path projects.

• Monitor delivery health metrics and implement improvements.

• Promote adoption through comprehensive documentation, reference architectures, self-service workflows, and enhancements to the developer experience.

• Define the technical vision, architecture, and long-term development of cloud platform products.

• Lead design and architecture reviews as well as technical deep dives.

• Assess and integrate emerging technologies in AI infrastructure, LLM gateways, agent runtimes, MCP/tool integration, model serving, and orchestration.

• Collaborate with architecture, security, and reliability teams to ensure compliance with enterprise standards.

• Establish SLOs, observability, alerting, runbooks, and readiness for on-call duties.

• Act as a technical escalation point for intricate production incidents and lead root cause analysis efforts.

• Design solutions for supportability, scalability, high availability, and cost-effectiveness.

• Mentor and grow engineers through coaching, design guidance, code reviews, and collaboration.

• Elevate engineering standards and delegate technical ownership to nurture technical leaders.

• Cultivate communities of practice in cloud-native development, agentic AI, and platform engineering.

⛳️ Requirements

• Must be at least eighteen years old.

• Must have legal authorization to work in the United States.

• Proficient in an object-oriented programming language, preferably Go.

• Extensive experience in designing, building, and delivering distributed cloud-native systems.

• Familiarity with Google Cloud Platform and Kubernetes (GKE) in a production setting.

• Proven experience leading architecture, technical decisions, and delivery across multiple applications or teams.

• Minimum of 7 years of relevant work experience.

• Bachelor’s degree or equivalent in a related field.

• Preferred: 8+ years of software engineering experience demonstrating technical leadership in large-scale platforms or distributed systems.

• In-depth expertise in Golang, Google Cloud, Kubernetes, IaC, GitOps, automation, CI/CD, progressive delivery, observability, cloud security, and platform engineering.

• Experience in building platforms for agentic AI workloads, including LLM gateways, agent runtimes, model serving, MCP integration, orchestration layers, and vector databases.

• Experience in designing developer platforms, APIs, and self-service experiences.

• Experience collaborating with SRE/Reliability Engineering to create highly available production systems.

• Experience leading enterprise architecture reviews and influencing technical directions across teams.

• Demonstrated ability to align engineering, product, architecture, security, and operations stakeholders.

• Proven capability to mentor engineers and enhance technical excellence within the organization.

• Experience in supporting highly available 24x7 retail platforms.

• Google Cloud Professional certifications are advantageous.

🏝️ Benefits

• Remote/Virtual work arrangement.

• Typically requires overnight travel of less than 10% of the time.

• Opportunities for professional development through technical coaching, design guidance, code reviews, collaborative work, continuous learning, and hands-on experimentation.

• Chance to engage with emerging technologies in AI infrastructure, agentic AI, and cloud platforms.