The opportunity
As a Staff Backend Engineer, you will provide technical leadership across your team and adjacent teams, solving the highest-scope and most complex problems in your area. You will lead large, cross-cutting backend initiatives, drive our modular architecture strategy, and define…
What you'll do
Lead Cross-Cutting Initiatives: Lead the technical design and delivery of large backend initiatives that span teams, and identify and remove systemic bottlenecks across product and infrastructure groups.
Own Architecture Strategy: Drive modular backend, service, data, and platform architecture. Lead modernization of the monolith and legacy backends toward modular, reusable, and appropriately independently operated systems — while preventing fragmentation and service sprawl.
Set the Standards: Define and improve standards for APIs, contracts, compatibility, schema evolution, testing, security, performance, observability, operability, and maintainability — plus the build, test, deploy, release, rollback, and production-readiness practices needed to operate modular features safely.
Establish Shared Patterns: Create the patterns for dependency management, data ownership, eventing, failure isolation, service maturity, and operational documentation. Establish Go service patterns and Kubernetes operating practices where they matter to our production estate, and guide Rust adoption where it solves a real systems, security, performance, or supply-chain problem.
Own What You Build in Production: Take part in on-call and incident response for the systems your teams own, act as a technical escalation point during complex incidents, and turn what you learn into architectural and operational improvements that prevent recurrence.
Influence and Partner: Shape technical direction across teams without formal authority, and partner with Product and Engineering leadership on platform-level roadmap decisions and investment trade-offs.
What they're looking for
- Grow Engineers: Mentor Senior and Intermediate engineers, shepherd technical debt reduction and reusable patterns that improve throughput, and raise the technical capability of the wider team.
- Lead AI Adoption: Lead team-level adoption of AI-assisted and agentic workflows, including the quality, security, privacy, and operational guardrails, and help engineers direct, validate, reject, and course-correct agent output.
