Requirements

6+ years of experience in systems software engineering, including distributed systems, storage systems, networking infrastructure, or OS-level components
Designing and implementing large-scale, production systems with set reliability, performance, and operational requirements
Debugging complex, non-reproducible systems issues using profilers, static analyzers, tracing frameworks, or custom instrumentation
Establishing observability for production systems through metrics, dashboards, alerting, and service level objectives
Driving cross-team technical projects from design to production, including dependency coordination, rollout planning, and post-launch monitoring

Nice to Haves

Familiarity with resiliency testing methodologies such as overload testing, chaos engineering, or fault injection
Ongoing AI skill development including prompt/context engineering and agent orchestration
Experience with systems programming languages like C, C++, Rust, or Go in production environments
Adherence to responsible, ethical AI practices including risk assessment and bias mitigation
Contributions to platform or infrastructure projects used by multiple teams
Improving developer productivity through tooling, automation, or codebase modernization at organizational scale
Integration of AI tools to optimize workflows and drive measurable impact such as efficiency or quality improvements

Designing and implementing scalable, reliable infrastructure components across distributed computing, storage, networking, or runtime environments
Owning end-to-end technical design, evaluating architectural trade-offs balancing performance, reliability, and maintainability
Instrumenting systems with telemetry, dashboards, and alerting to identify performance bottlenecks and failure modes
Leading incident response, root cause analysis, and authoring retrospectives with follow-up improvements
Defining and enforcing service level objectives and building debugging and mitigation playbooks
Collaborating with product engineering, infrastructure, and security teams to meet privacy, security, and integrity needs
Driving engineering efficiency via tooling, automation, and eliminating legacy technical debt
Mentoring engineers on systems design, coding standards, and operational best practices; contributing to recruiting and technical programs
Analyzing performance profiles to identify hotspots and implement targeted optimizations
Communicating technical decisions, trade-offs, and project status to stakeholders at various levels