Principal Software Engineer

Full Job Description

Architect and develop distributed control-plane services for provisioning, orchestration and lifecycle management of AI accelerator infrastructure. Design scalable systems for state management, health monitoring, reconciliation and fault recovery. Build host and device management software connecting cloud infrastructure with operating systems, drivers, firmware and accelerator devices. Develop infrastructure supporting accelerator virtualisation, device assignment, isolation and resource management. Integrate accelerator infrastructure with Kubernetes and cloud-native platforms. Design robust APIs and abstractions across cloud services, host software and device interfaces. Drive improvements in reliability, security, observability, diagnostics, testing and operational readiness. Champion AI-assisted engineering practices across architecture, design, coding, testing, debugging, code reviews and documentation to improve engineering velocity and software quality. Apply AI-assisted workflows to accelerate code comprehension, root-cause analysis, test development, design exploration and engineering automation. Identify opportunities to integrate AI into engineering workflows to reduce repetitive work, shorten development feedback loops and improve developer effectiveness. Use AI-assisted learning together with engineering fundamentals to accelerate development of systems, hardware and AI infrastructure domain competency. Establish reusable engineering practices and mentor engineers on the responsible and effective application of AI throughout the software development lifecycle. Diagnose complex system issues spanning distributed services, operating systems, host software, drivers, firmware and hardware. Lead architecture and design reviews, solve complex cross-layer system issues and mentor engineers. Collaborate across hardware, firmware, OS, cloud infrastructure and AI platform teams to deliver end-to-end solutions. Partner with hardware, firmware, operating system, cloud infrastructure and AI platform teams to deliver end-to-end solutions. Mentor engineers and contribute to raising the technical capabilities and engineering standards of the broader organisation. Bachelor's Degree in Computer Science, Computer Engineering or related technical discipline, or equivalent experience with at least 12+ years of relevant industry experience. Software engineering experience in C++, C, C#, Rust, Go or similar languages. Experience designing and developing distributed systems, cloud infrastructure or systems software. Understanding of concurrency, state management, asynchronous programming and failure recovery. Experience building reliable production software with strong debugging and problem-solving skills. Demonstrated technical leadership across complex, multi-team engineering projects. Ability to leverage AI-assisted engineering tools and workflows, combined with strong engineering judgement, to improve software development effectiveness, quality and technical problem solving. Ability to rapidly develop expertise in complex technical domains and help raise engineering competency across the team through mentoring, technical guidance and knowledge sharing. Experience with cloud control planes, resource orchestration or infrastructure management systems. Experience with GPU, AI accelerator or heterogeneous compute infrastructure. Knowledge of PCIe, SR-IOV, PF/VF, device virtualisation or device passthrough. Experience with host/device agents, Linux systems software, device drivers or firmware interfaces. Experience with hardware lifecycle management, health monitoring and fault recovery. Experience with telemetry, observability and debugging large-scale production systems. Experience applying AI-assisted software engineering to design, development, code comprehension, debugging, testing, documentation or engineering automation. Experience identifying and developing AI-enabled engineering workflows that improve developer productivity and reduce repetitive engineering effort. Experience using AI-assisted approaches to accelerate understanding of large and complex codebases, system architectures and cross-layer technical issues. Experience establishing engineering practices that help teams adopt AI effectively while maintaining code quality, security, correctness and engineering accountability. AIINFRA This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. *