Member of Technical Staff (Backend/Infrastructure Engineer, Search)

The role

This engineer sits on the team that runs Perplexity's search backend, where response speed matters most. The work spans Rust and Go code, retrieval infrastructure, cloud platforms, and monitoring, and the person is expected to carry systems from initial design through live operation.

What you would do

• Stand up and maintain low-latency infrastructure that serves search queries and retrieval traffic.
• Evolve distributed backend services so they keep working under heavy load.
• Troubleshoot Linux hosts, container runtimes, network paths, and live services.
• Raise reliability through monitoring, forecasting capacity needs, profiling performance, and handling outages.
• Run cloud workloads mainly on AWS and Kubernetes.
• Write internal tooling that speeds up building, testing, debugging, and operating infrastructure.
• Refine build pipelines, release workflows, and safe rollout practices for production.
• Ship changes into product code written in Rust, Go, and other low-level languages.
• Take ownership of a system from architecture through deployment and ongoing operation.

What they asked for

• Solid hands-on background with cloud platforms, distributed architectures, and automation.
• Thorough grasp of Linux kernel behavior, performance diagnosis, and debugging in production.
• Track record building or running backend services that demand low latency and high throughput.
• Working knowledge of containerization, orchestration, observability tooling, and declarative infrastructure definitions.
• Prior work building or sustaining continuous integration and delivery systems and release tooling.
• Strong command of one low-level language; the accepted list includes Java, C++, Go, and Rust.
• Comfortable moving between infrastructure concerns and application code without friction.
• Takes initiative and accountability, adapting quickly when priorities shift in a fast-paced setting.

Nice to have

• Exposure to search, retrieval, ranking, or other systems that serve large datasets.
• Running Rust services in a production environment.
• Hands-on work with AWS, Kubernetes, and contemporary observability platforms.
• Experience with profiling, forecasting capacity, and tuning performance.
• Building developer or operations tools that rely on AI assistance.