Principal Software Engineer – Backend Platform Engineering

Job Description

Principal Software Development Engineer – Rust | Confidential Employer

The Tone:
This is a hybrid role at Zscaler, a company pioneering security transformation in the AI era. Zscaler builds the Zscaler Zero Trust Exchange platform, the world’s largest in-line cloud security platform, to protect thousands of customers from cyberattacks and data loss. This role is crucial for designing and scaling high-performance backend services using Rust to drive the evolution of Zscaler’s converged platform, contributing to an AI-native enterprise where human potential is amplified by machine intelligence.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: Hybrid

• Team: Platform Convergence department, reporting to the Sr. Director of Software Engineering
• Mission: Design and scale high-performance backend services to drive the evolution of the converged platform.
• Tech Stack: Rust, async/await, gRPC, Protobufs, Tokio, async-std, C/C++, Go, eBPF, XDP, DPDK, TCP/IP, UDP, QUIC

What You’ll Actually Do
• Design and build a low-latency, high-throughput data forwarding plane using Rust and async/await models for efficient service-oriented infrastructure.
• Develop distributed, scalable systems with a heavy focus on concurrency, fault tolerance, and messaging.
• Implement and maintain gRPC-based APIs and services to integrate forwarding plane capabilities with control and orchestration layers.
• Optimize system performance through deep profiling across kernel-space and user-space.
• Drive technical excellence through code reviews, architectural discussions, documentation, and mentoring junior engineers.

The Must-Haves
• Background: Principal-level professional with a foundational understanding of AI/ML technologies.
• Experience: 14+ years of software development experience, specializing in systems programming and Rust, with extensive experience in async frameworks such as Tokio or async-std, and a proven track record of building resilient, observable, and horizontally scalable distributed systems.
• Skills: Deep understanding of Linux fundamentals, networking, container-based environments, CI/CD, and kernel-user space interaction; ability to leverage AI-driven solutions to optimize outcomes within a functional domain.
• Bonus: Professional experience with systems languages like C/C++ or Go in performance-critical environments; hands-on experience with kernel-space technologies such as eBPF, XDP, or DPDK; professional experience with gRPC, Protobufs, and L2–L4 networking protocols including TCP/IP, UDP, and QUIC; experience leveraging AI-assisted developer tools, automated profiling, or AI acceleration libraries.