Staff / Senior Software Engineer, Infrastructure
Builds and operates scalable infrastructure systems including Kubernetes clusters, distributed databases, and cloud services to support AI music platform at consumer scale. Requires 5+ years experience in infrastructure engineering with strong ownership and scaling expertise.
About the job
What You’ll Do
- Architect and build services to handle massive consumer traffic, data, and usage
- Design systems that are performant, secure, scalable, and easy to observe
- Own systems end-to-end — from design and implementation through deployment, monitoring, and operational excellence
- Lead by example on engineering excellence — code quality, system design, documentation, and operational maturity
- Collaborate with engineering teams across the company to understand their needs and build the right abstractions
- Communicate proactively and with high bandwidth — concise and information-dense async updates, stakeholder alignment, low entropy
- Operate with ambiguity — scope what matters, make tradeoffs, and drive projects forward independently
What You’ll Need (Required)
- 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
- Experience with some combination of: Kubernetes, Docker, infrastructure as code (Pulumi/Terraform/CDK), databases (Postgres, distributed relational databases), caching systems, or container orchestration
- Ability to reason through hard scaling, reliability, and performance problems with clear technical judgment
- High ownership — you drive projects end-to-end without waiting for direction
- Strong communication skills — you keep stakeholders informed and reduce ambiguity for the teams you serve
- An obsession with engineering excellence, iterating and learning rapidly, and working hard
Strong Plusses
- Deep experience with Kubernetes at scale — cluster management, control plane scaling, multi-tenancy
- Experience with large-scale databases, distributed data layers, or storage systems
- Experience with ML infrastructure — inference serving, ML data pipelines, MLOps, GPU infrastructure
- Experience on a platform or developer experience team where your primary customers were other engineers
- Experience building internal systems 0→1 (auth, notifications, CDN, DevEx tooling, or similar)
- Strong oncall instincts — triage, debug, and resolve incidents across a distributed stack
- Hands-on familiarity with AI tooling and the current landscape of AI for software engineering — models, agents, coding assistants, and agentic workflows
- Golang or Rust experience, especially for large-scale systems
- Experience with websockets, CDNs, streaming traffic patterns, and audio/video delivery
- Security best practices in building and scaling infrastructure
- Technical leadership or management experience
Skills
Kubernetes, Docker, AWS, GCP, Terraform, Pulumi, Postgres, Go, Rust, Distributed Systems
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