Systems Software Engineer - Richardson, TX, United States

Originally posted 3 October 2026 by the employer.

About the role

This role involves architecting, designing, and developing software to enable and demonstrate the value of future memory and storage technologies. You will contribute across multiple layers of AI and systems software stacks, from AI applications to hardware/software interfaces.

What you'll do

• Design and modify AI inference software stacks to enable proof-of-concept hardware capabilities.
• Develop software to quantify and demonstrate the value of proposed system features.
• Lead software architecture and development efforts, both independently and as a technical lead for small teams.
• Research emerging AI software topics to identify memory and storage system challenges and opportunities.
• Develop and modify Linux applications and libraries using C, C++, Python, Rust, CUDA, and/or SYCL for advanced heterogeneous computing systems.
• Debug system-level issues spanning applications, libraries, operating systems, kernels, system configuration, networks, and hardware/software interfaces.

What you'll need

• Bachelor’s or Master’s degree with 10+ years of experience, or a PhD with 7+ years of experience, in Computer Science, Software Engineering, Computer Engineering, or a related field.
• Working knowledge of end-to-end AI inference software stack architectures, with hands-on development experience in multiple layers, such as frameworks, inference engines, ML compilers, compiler infrastructure, hardware runtimes, or hardware abstraction layers.
• Experience debugging issues spanning applications, libraries, operating systems, kernels, networks, and hardware/software interfaces.
• Proficient development skills in C, C++ and Python, with Linux-specific programming experience such as multithreading, IPC, ioctl, GDB, and the /proc and /sys filesystems.
• Experience programming GPUs or other accelerators using CUDA, SYCL, OpenCL, or a comparable programming model.
• Familiarity with LLM serving internals, including KV-cache management, prefill and decode phases, KV-cache offloading, and disaggregated serving.
• Strong understanding of heterogeneous compute architecture concepts, including memory hierarchies, NUMA, caching, accelerator architectures, and interconnects such as PCIe, CXL, NVLink, or UALink.

Nice to have

• Technical leadership experience in a systems-focused pathfinding or research organization.
• Technical knowledge of HBM, DRAM, and emerging memory technologies.

Skills: AI inference software stacks, heterogeneous computing, CUDA, SYCL, Linux applications, LLM serving