We are hiring a Staff Backend Software Engineer to own the architecture and scaling of our core platform. This is a hands-on role: you will design and ship the systems that everything else is built on, set the technical bar for the backend team, and make the build-vs-buy and architecture calls that a company only gets to make once. You will report directly to (VP Engineering / CTO) and work with founders on technical direction.
What You Will Do
- Design, build, and operate distributed backend systems that scale with the business: APIs, data pipelines, and core services with real reliability and latency requirements.
- Own major architectural decisions end to end: technology choices, service boundaries, data modeling, and migration paths.
- Set the engineering standard: raise code quality, drive design reviews, and mentor senior and mid-level engineers without becoming a full-time manager.
- Work directly with product and founders to turn ambiguous business problems into shipped systems, fast.
- Carry production ownership: instrumentation, on-call, incident response, and postmortems that actually change the system.
What We Look For
- 8+ years building backend systems in production, with clear evidence of increasing scope and technical ownership.
- A track record at companies known for a high engineering bar: top-tier technology companies, high-growth startups, or equivalently demanding environments where you shipped systems at scale.
- Deep expertise in at least one modern backend language (Go, Java, Python, Rust, or similar) and strong distributed-systems fundamentals: consistency, queuing, caching, observability.
- Experience owning architecture for systems serving significant scale (high throughput, large data volumes, or strict latency budgets) and living with the consequences of your decisions.
- Strong computer science foundations. Many of our engineers come from top CS programs; what matters is that you reason from first principles, not that you memorized a syllabus.
- Bias for shipping. You have operated in environments where speed mattered and quality was not negotiable, and you know how to hold both.
Nice to Have
- Experience taking a system from single-service to distributed, or from thousands to millions of users.
- Exposure to ML/AI infrastructure, data-intensive platforms, or event-driven architectures.
- Prior startup experience at Series A-C stage, or founding-engineer scope at a larger company.