Staff Software Engineer, Edge

What you’ll do

• Build Edge systems that combine in-house implementation, open-source software like Envoy proxy, and multiple CDN & DNS providers. Balance what to build, what to leverage from the community, and what to orchestrate across vendors.
• Drive automation traffic management efforts in the Edge space, designing solutions to manage bots and crawlers at scale.
• Design and implement request processing logic in Envoy to support Edge capabilities such as routing, traffic classification, and enforcement. Write, review, and maintain code written in C++, Golang, and Python.
• Collaborate with CDN vendors and internal platform teams to define integration points.
• Study internal user pain points with the rate limiting platform and translate findings into a prioritized roadmap.
• Mentor engineers within the team and demonstrate technical leadership through design reviews, pairing, and coaching.
• Use AI to accelerate prototyping, analysis, and operational tasks, while applying engineering judgment to verify correctness and production-readiness.
• Participate in oncall for Edge systems and drive incident response, post-mortems, and reliability improvements.

What we’re looking for

• 6+ years of experience in infrastructure, networking, or platform engineering, with a deep focus on traffic management systems (CDN, HTTP gateways, service mesh, or load balancing).
• Experience with bot detection, scraping prevention, or automation traffic management systems is a plus.
• Proficiency in C++, Golang, or Python, with experience developing L7 HTTP proxies such as Envoy, Nginx, Varnish, and Traefik.
• Deep understanding of network protocols across L3-L7 and hands-on experience debugging production networking issues at scale.
• Experience gathering requirements from internal users, aligning cross-functional stakeholders, and delivering credible technical plans.
• Proven ability to design distributed systems architectures and drive them from proposal through proof of concept to production.
• Demonstrated experience using AI to accelerate engineering workflows (design exploration, code generation, operational analysis), with a clear approach to validating correctness and quality.
• Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.