Member of Technical Staff, Traffic Infrastructure

The Role:

As a Member of Technical Staff on our Traffic Infrastructure team, you will own the traffic layer behind our generative AI platform: the proxies, load balancers, service mesh, and routing systems that move every request reliably across regions and cloud providers. This is a highly technical role that calls for depth in distributed systems, cloud networking, and infrastructure, along with the judgment to balance latency, cost, and operational simplicity. You will partner closely with ML, product, and platform teams, and help set the technical direction for the team.

Key Responsibilities:

• Architect and build scalable, fault-tolerant traffic and networking services, including ingress and egress, load balancing, routing, and quality-of-service controls.

• Lead technical design discussions, mentor other engineers, and establish best practices for operating large-scale infrastructure.

• Drive network optimization both inside and outside data centers, including cost reduction, performance tuning, and removing scaling bottlenecks.

• Evaluate and integrate cloud-native and open-source technologies (e.g., Kubernetes, Envoy, Istio) to strengthen platform capabilities and reliability.

• Own systems end to end, from design through deployment and observability, with an emphasis on high availability, disaster recovery, and operational excellence.

• Develop and maintain comprehensive monitoring, alerting, logging, and tracing to give deep insight into system health and performance.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).

• 5+ years of experience building backend or network infrastructure in cloud environments (e.g., AWS, GCP, Azure).

• Strong software development skills in languages such as Go, C++, Rust, Java, or Python.

• Deep understanding of distributed systems and networking fundamentals, including performance optimization.

• Full product lifecycle ownership, from design through implementation to production.

Preferred Qualifications:

• Master's or PhD in Computer Science or a related field.

• Hands-on experience with traffic or edge engineering, service mesh, or cloud networking (e.g., Envoy, Istio, DPDK).

• Deep Kubernetes experience, including ingress, network policy, and custom controllers.

• Track record of improving performance, reliability, and cost-efficiency on high-throughput systems.

• Experience leading projects across teams and coaching distributed engineers.

Why Fireworks?

• Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.