Compiler Performance Engineer at Azul Systems

Azul Systems is a pioneer in high‑performance Java runtimes, trusted by enterprises that demand low‑latency and scalable services. As a Compiler Performance Engineer, you’ll be at the heart of Falcon, a JIT compiler that pushes the limits of Java execution, giving you a unique platform to influence the performance of mission‑critical applications worldwide. Working here means access to cutting‑edge research, direct impact on open‑source LLVM projects, and the chance to collaborate with world‑class compiler architects across continents. Beyond the technical allure, Azul offers a culture that values deep expertise while encouraging rapid skill growth. The Bangalore office blends a vibrant startup spirit with the stability of an established leader, providing mentorship, continuous learning budgets, and opportunities to present your work at global conferences. This role can accelerate your career trajectory, positioning you as a go‑to expert in JIT compilation and performance engineering within the broader JVM ecosystem.

Prepare by mastering the fundamentals of Java execution: study the HotSpot compilation pipeline, understand how tiered compilation works, and be ready to discuss trade‑offs between interpreter, C1, and C2. Dive into LLVM’s architecture—focus on how front‑ends generate IR, how optimization passes are applied, and how back‑ends emit machine code for x86_64 and AArch64. Build a small project that modifies an LLVM pass or writes a simple JIT to demonstrate hands‑on competence. During the interview, expect performance‑focused coding challenges that require you to profile a Java micro‑benchmark, identify bottlenecks, and propose concrete optimizations. Practice explaining your reasoning clearly, referencing hardware counters, cache behavior, and instruction‑level parallelism. Additionally, be prepared for system‑design questions around building a scalable benchmarking framework for enterprise workloads, and showcase your ability to collaborate across time zones by describing past experiences in distributed teams.