Senior Software Engineer

Design and develop AI Accelerator Agent software for device configuration, monitoring and lifecycle management. Build scalable communication between control-plane services, host agents and accelerator devices. Develop and optimise networking for high throughput, low latency and resilient distributed communication. Enable accelerator software across pre-silicon platforms, including FPGA, emulation, simulation and virtual platforms, through post-silicon hardware. Develop device-enablement software integrating with operating systems, drivers, firmware and accelerator hardware. Build AI hardware infrastructure capabilities and tools for node provisioning, configuration, health monitoring, diagnostics and lifecycle management. Develop robust mechanisms for device health, state management, fault detection and recovery. Collaborate across cloud, networking, driver, firmware, hardware and infrastructure teams to deliver end-to-end solutions. Apply AI-assisted engineering practices across architecture, design, development, testing, debugging and documentation to improve engineering velocity and software quality. Use AI-assisted workflows to accelerate code comprehension, network performance analysis, root-cause investigation, test development and systems debugging. Leverage AI to automate repetitive engineering workflows and accelerate diagnosis of complex distributed-system, networking and device-level issues. Use AI-assisted learning to deepen expertise across distributed systems, networking, accelerator architecture, drivers, firmware and hardware infrastructure. Develop and share reusable AI-assisted engineering practices that improve team productivity, technical learning and domain competency. Bachelor's Degree in Computer Science, Computer Engineering or related technical field, or equivalent experience with 8+ years of industry relevant experience. Strong programming skills in C/C++, C#, Rust, Go or similar systems programming languages. Experience developing systems software, distributed systems or device-enablement software. Strong knowledge of computer networking, network protocols, distributed communication, throughput and latency optimisation. Experience enabling software across hardware development or validation environments, including pre-silicon and/or post-silicon platforms. Strong understanding of concurrency, asynchronous programming, reliability, state management and failure recovery. Ability to effectively apply AI-assisted engineering tools and workflows to improve development velocity, debugging, testing and engineering quality. Experience developing host/device agents or AI accelerator management software. Experience with GPU, AI accelerator or heterogeneous compute infrastructure. Experience with FPGA, hardware emulation, simulation or virtual platform environments. Experience building infrastructure or tooling for compute-node provisioning, health management, diagnostics and device lifecycle management. Experience with high-performance networking and large-scale distributed systems. Experience with Linux, device drivers, firmware interfaces, PCIe, SR-IOV, PF/VF or device virtualisation. Experience with telemetry, profiling, tracing and performance diagnostics. Experience applying AI-assisted engineering to code analysis, network/system performance investigations, debugging, testing and engineering automation. Experience using AI-enabled workflows to rapidly build technical expertise across complex systems and hardware domains AIINFRA This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. *