[Hiring] Systems Software Engineer @The AES Group

Role Description

Our client is building the interoperability layer for AI infrastructure. Their mission is to eliminate software and hardware incompatibility across the AI ecosystem, enabling AI applications to run on any accelerator, any server, and any data center. They are tackling one of the largest challenges in AI computing today: hardware lock-in and fragmented software ecosystems. Their platform combines systems software, orchestration, translation technologies, and hardware acceleration to unlock the next generation of AI infrastructure.

They are looking for a highly technical Systems Software Engineer who loves working across the entire technology stack—from kernel-level programming and operating systems to distributed services and application layers. This role is ideal for someone who enjoys solving hard systems problems, wants to learn deeply about AI and High-Performance Computing (HPC), and is excited to help build infrastructure that operates at data-center scale. You will work alongside experienced architects and engineers who have built large-scale systems at some of the world’s leading technology companies and AI infrastructure providers.

Qualifications

• Strong proficiency in C++ and/or Rust.
• Deep understanding of Linux operating systems and systems programming.
• Experience with multithreading, concurrency, memory management, and performance optimization.
• Strong debugging and problem-solving skills.
• Comfortable reading and understanding complex codebases.
• Curiosity and willingness to learn new technologies rapidly.
• Passion for building infrastructure and solving challenging technical problems.

Requirements

• Develop high-performance systems software in C++ and Rust.
• Work across Linux kernels, drivers, runtimes, operating systems, services, and applications.
• Design and optimize software for AI and HPC workloads.
• Build components that interface with GPUs, accelerators, networking, and storage systems.
• Develop distributed services that operate across large-scale compute environments.
• Investigate performance bottlenecks and optimize systems for throughput, latency, and efficiency.
• Collaborate with hardware, platform, and AI engineers to build next-generation infrastructure.
• Participate in architecture, design reviews, debugging, and performance analysis.

Benefits

• AI infrastructure at hyperscale.
• HPC architecture and optimization.
• GPU and accelerator technologies.
• Distributed computing platforms.
• Advanced systems software design.
• Data center-scale infrastructure engineering.
• Emerging AI hardware ecosystems.

Company Description

Note: Open for PhD candidates with relevant research experience.