Software Engineer - Cloud Platform

Zero Motorcycles•Scotts Valley, CA

23h•Onsite

About The Position

We build electric motorcycles. The ride feels simple and alive. The rest should be too. We are not there yet. You will help us get there. The Product Experience team is responsible for how the motorcycle feels to use. We design and build the firmware that runs on the bike, the dash the rider sees, the mobile app they carry, the diagnostic tools used in the field, and the cloud systems that connect them. Our cloud platform carries telemetry from the bike, powers the tools our technicians depend on, and keeps the mobile app connected. It already sits in the critical path for multiple programs, and we are still shaping how it behaves. The engineering decisions we make now will determine what we can enable for our riders and the business, and how fast we can do it.

Requirements

4 - 9 years of experience designing, operating, and debugging distributed cloud systems in production, where failures have real consequences and root cause isn't always obvious.
Worked in systems that are in use, not fully understood, and under pressure, and know how to work with stakeholders to articulate tradeoffs and decide what actually needs to be fixed now versus what can wait.
Consistent and dependable in delivering high-quality code and maintaining critical system uptime across systems that multiple programs depend on.
Extensive experience developing in Python, with a focus on FastAPI and building clean, maintainable backend systems.
Proficiency with Next.js and modern React-based frontend development.
Deep fluency with the AWS ecosystem across EC2, RDS, DynamoDB, S3, and Lambda.
Expertise in AWS CDK in Typescript, with the ability to provision and manage complex infrastructure through code.
Familiarity with Git and automated deployment workflows.
Documents decisions, designs, and system behavior as you go, so the next person doesn't have to rediscover what you already know.
Experience building automated test suites that catch integration risk before it reaches production.
Proficiency debugging distributed systems and reading cloud-native logs to identify and resolve bottlenecks before they surface in the field.
Ability to translate technical tradeoffs into consequences the business can understand, not just what is technically correct, but what each decision costs and enables over time.
Experience presenting technical work to leadership and contributing to decisions about where the system goes next.
Can move from system design to implementation to debugging without losing the thread between them.
Self-directed on high-level problems, able to take a poorly defined system concern and work it through to a clear solution without requiring close oversight.
Fluent with AI-assisted development tools and uses them to move faster and think more clearly, without substituting them for the engineering judgment this role requires.

Responsibilities

Own the cloud systems that move data between the motorcycle, the mobile app, and the tools technicians use in the field, from the infrastructure they run on to the pipelines that deploy them.
Decide what problems need to be solved next, and work with the architects to ensure they are framed and addressed well.
Mentor junior and mid-level engineers on Python, AWS, and system design, and the quality of that mentorship shows up in what the team is able to do without you.
Work with architects to shape how the platform is structured so that teams building on top of it can move independently without breaking each other.
Own the connectivity between the FastAPI backend, Next.js frontend, and the AWS infrastructure that connects them, and ensure that boundary stays clean as the system grows.
Own the compute strategy across the AWS stack, making deliberate decisions about when each service is the right tool given the tradeoffs in cost, reliability, and operational complexity as usage scales.
Analyze and enhance system resources to ensure high availability and scalability of production environments as fleet size and program dependencies grow.
Keep infrastructure reproducible and deployable through AWS CDK, so that what runs in production can be understood, changed, and recovered from code.
Own the CI/CD pipeline as a first-class system concern, not an operational afterthought. How fast the team can validate a change, catch a regression, and recover from a bad deploy is determined here.
Make the pipeline safe enough and fast enough that shipping a fix is never the reason a problem stays in the field longer than it should.
Design the test strategy so that integration risk is caught before deployment, not discovered by a technician or rider.
Build and maintain the observability layer so that when something breaks, the signal is visible immediately and the cause is diagnosable without archaeology.
Treat escaped defects as system failures, not individual mistakes, and use them to drive improvements in how the platform detects and contains problems earlier.
Own the data layer across RDS, DynamoDB, and S3, and ensure it holds under the load of multiple programs depending on it simultaneously.
Review existing data pipelines and lead the effort to scale them to support analytics and machine learning as the business demands more from the data it already collects.
Participate in shaping the company's data strategy so that what we instrument today supports the product decisions we need to make next year.
Work directly with Battery, Firmware, Mobile Apps, Diagnostic Tools, Customer Support, Field Quality, and other teams to reduce the handoff and coordination costs of getting what they need from the platform.
Present work to leadership and participate in defining future initiatives, because the person closest to how the system behaves should have a voice in where it goes next.
Mentor junior and mid-level engineers on Python, AWS, and system design, and hold the bar on what good looks like in code review, architecture discussions, and how problems get framed.