Cloud Native Engineer at Zettabyte

Job description

WHY THIS ROLE EXISTS We're looking for a Cloud Native Engineer to build and optimize the microservices architecture powering our AI cloud platform. You'll design resilient, scalable systems using cutting-edge cloud native technologies, ensuring our platform can handle massive AI workloads with reliability and performance. As part of our cloud native engineering team, you'll work on Kubernetes-based infrastructure, Go microservices, and container orchestration systems that serve as the backbone of our AI computing platform. You'll architect the systems that make AI compute seamless for thousands of developers and enterprises. This is a unique opportunity for someone who's excited to work with the latest cloud native technologies, solve complex distributed systems challenges, and build infrastructure at scale in the rapidly growing AI space. WHAT YOU'LL DO - Design and develop microservices using Go that power our AI cloud platform's core functionality - Build and maintain Kubernetes-based infrastructure for container orchestration and workload management - Implement and optimize cloud native solutions for scalability, reliability, and performance - Contribute to code reviews, technical documentation, and knowledge sharing within the engineering team - Explore and integrate emerging cloud native technologies like Volcano, Prometheus, and service mesh solutions - Design distributed systems architecture for high-availability AI workload processing - Collaborate with DevOps and SRE teams to ensure production reliability and monitoring - Leverage AI-assisted coding tools (GitHub Copilot, ChatGPT, Cursor IDE, etc.) to boost productivity and code quality YOU'LL THRIVE HERE IF YOU - 7+ years of software engineering experience with focus on distributed systems and cloud native technologies - Strong proficiency in Go with deep understanding of concurrency patterns and standard libraries - Familiarity with Python or other backend languages for polyglot development environments - Hands-on Kubernetes experience including development, deployment, and maintenance of production clusters - Solid understanding of microservices architecture design patterns and implementation best practices - Experience with containerization technologies (Docker, containerd) and container runtime optimization - Problem-solving mindset with ability to independently design and implement complex system components - Strong collaboration and communication skills for working in cross-functional teams - Experience using AI-assisted coding tools and willingness to integrate them into development workflow BONUS QUALIFICATIONS - Familiarity with cloud native ecosystem tools such as Prometheus, Grafana, Volcano, or service mesh technologies - Open source contributions to cloud native projects (Kubernetes, CNCF ecosystem) - Experience with large-scale Kubernetes cluster operations and troubleshooting in production environments - Knowledge of microservices architecture patterns including circuit breakers, service discovery, and distributed tracing COMPENSATION - We provide Competitive salary and equity based on your experience and skillset; - This is a Hybrid role - 3 days in office, 2 days WFH; Must locate in Palo Alto - Applicants must be authorized to work in the United States without need for visa sponsorship.

Requirements

Must-haves

This is a unique opportunity for someone who's excited to work with the latest cloud native technologies, solve complex distributed systems challenges, and build infrastructure at scale in the rapidly growing AI space.
Design and develop microservices using Go that power our AI cloud platform's core functionality
Build and maintain Kubernetes-based infrastructure for container orchestration and workload management
Implement and optimize cloud native solutions for scalability, reliability, and performance
Contribute to code reviews, technical documentation, and knowledge sharing within the engineering team
Explore and integrate emerging cloud native technologies like Volcano, Prometheus, and service mesh solutions
Design distributed systems architecture for high-availability AI workload processing
Collaborate with DevOps and SRE teams to ensure production reliability and monitoring
Leverage AI-assisted coding tools (GitHub Copilot, ChatGPT, Cursor IDE, etc.) to boost productivity and code quality
7+ years of software engineering experience with focus on distributed systems and cloud native technologies
Strong proficiency in Go with deep understanding of concurrency patterns and standard libraries
Familiarity with Python or other backend languages for polyglot development environments
Hands-on Kubernetes experience including development, deployment, and maintenance of production clusters
Solid understanding of microservices architecture design patterns and implementation best practices
Experience with containerization technologies (Docker, containerd) and container runtime optimization
Problem-solving mindset with ability to independently design and implement complex system components
Strong collaboration and communication skills for working in cross-functional teams
Experience using AI-assisted coding tools and willingness to integrate them into development workflow
Familiarity with cloud native ecosystem tools such as Prometheus, Grafana, Volcano, or service mesh technologies
Open source contributions to cloud native projects (Kubernetes, CNCF ecosystem)
Experience with large-scale Kubernetes cluster operations and troubleshooting in production environments
Knowledge of microservices architecture patterns including circuit breakers, service discovery, and distributed tracing

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aikubernetesgopythondocker

Platform: ashby
Effort: quick