On one of Suno’s platform teams, you’ll work on a subset of the complex challenges outlined below:
Build the platforms that 70+ engineers depend on to ship product quickly and safely — APIs, authentication, deployment tooling, backend-driven configuration, and similar
Manage migrations that help teams transition off legacy systems seamlessly and without risk
Collaborate with engineering teams across the company to understand their needs and build the right abstractions
Build shared infrastructure, agentic tooling, and workflows that enable AI-native development across the company
Define best practices, frameworks, and evaluation systems for how Suno uses tooling in daily work
Partner closely with engineering and non-engineering teams to understand their needs and build the right solutions
Architect and build services to handle write-heavy consumer traffic and data
Design systems that are performant, secure, scalable, and easy to observe
Build and operate distributed databases, caching layers, and storage systems at consumer scale
Scale Kubernetes infrastructure and control planes to support rapid product and ML growth
Design inference infrastructure that keeps AI workloads fast, reliable, and cost-efficient
Operate with ambiguity — scope what matters, move fast, and drive projects forward independently as the space evolves
Own systems end-to-end — from design through deployment, monitoring, and operational excellence
Mentor other engineers and raise the bar for engineering quality, reliability, and maintainability. #
What You’ll Need
To succeed on one of Suno’s platform teams, your experience and skill set might resemble a cross section of the following:
5–7+ years of infrastructure, backend, or systems engineering experience
Experience building and operating systems at significant scale in production
Strong understanding of distributed systems, cloud services (AWS/GCP), and modern infrastructure patterns
Expertise in infrastructure and platform security best practices
Ability to reason through hard scaling, reliability, and performance problems with clear technical judgment
Technical leadership or management experience
Experience building internal systems 0→1 — auth, notifications, CDN, or similar
Experience with websockets, streaming traffic patterns, and audio/video delivery
Familiarity with backend API design patterns at scale to serve internal backend, web and mobile clients alike
Experience on a platform or developer experience team where your primary customers were other engineers
Ability to manage system migrations with multiple dependent engineering teams
A working knowledge of security best practices in building and scaling infrastructure
Hands-on familiarity with the current landscape of AI for software engineering including, but not limited to: models, agents, coding assistants, and agentic workflows
Strong product instincts — you synthesize user needs and build the right abstraction
Comfort operating in ambiguous, fast-moving problem spaces
High ownership — you drive projects end-to-end without waiting for direction
Strong product instincts — you synthesize user needs and build the right abstraction
Strong communication skills — you keep stakeholders informed and reduce ambiguity for the teams you serve
Strong written communication — patient and educator-minded when rolling out tools that change how people work
Strong oncall instincts — triage, debug, and resolve incidents across a distributed stack
A love of music, whether you’re an avid listener or musician yourself
Additional Notes
This role is based in Cambridge, MA (Boston). - Applicants must be eligible to work in the US. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the Massachusetts Fair Chance in Employment Act, NYC Fair Chance Act, LA City Fair Chance Ordinance, and San Francisco Fair Chance Ordinance.
