Senior Engineer-Cloud AI Infrastructure

<p><strong><span style="font-size:1.2em"><span style="color:#121317">Huawei Canada&nbsp;has an immediate permanent opening for a Senior Engineer.</span></span></strong></p><p style="min-height: 1.7em;"></p><p style="text-align:start;"><strong><span style="font-size:1.2em"><span style="color:#121317">About the team:</span></span></strong></p><p class="MsoNormal"><span style="font-size:1.1em"><span style="color:#121317">Established in 2014, the Distributed Scheduling and Data Engine Lab is Huawei Cloud's technical innovation center in Canada. The lab focuses on researching and developing advanced cloud technologies, supporting the productization and iterative optimization of its technical achievements. Current research areas include cloud native databases, intelligent SQL engine, AI/Agent infrastructure and LLM/Agent Evaluation Technology. The lab fosters a robust technical environment, allowing collaboration with industry experts to create a highly competitive cloud platform.</span></span><span style="color:#121317">&nbsp;</span></p><p style="min-height: 1.7em;"></p><p class="MsoNormal"><strong><span style="font-size:1.2em"><span style="color:#121317">About the job:</span></span></strong></p><ul><li><p><span style="font-size:1.1em"><span style="color:#121317">Join a cutting-edge team building next-generation infrastructure for AI and agentic workloads, sitting at the intersection of research, systems engineering, and product innovation</span></span></p></li><li><p><span style="font-size:1.1em"><span style="color:#121317">Track and analyze the latest trends in LLMs, agentic AI, and multi-step agent workflows to inform infrastructure direction</span></span></p></li><li><p><span style="font-size:1.1em"><span style="color:#121317">Investigate and address infrastructure bottlenecks across GPU/NPU utilization, data movement, memory hierarchy, and distributed execution</span></span></p></li><li><p><span style="font-size:1.1em"><span style="color:#121317">Design system-level architectures for agent execution frameworks, multi-model orchestration, and large-scale inference systems</span></span></p></li><li><p><span style="font-size:1.1em"><span style="color:#121317">Evaluate AI/agent workload requirements on cloud and hybrid infrastructure, balancing trade-offs across cost, performance, and scalability</span></span></p></li><li><p><span style="font-size:1.1em"><span style="color:#121317">Deep dive into the full infrastructure stack — from distributed schedulers and inference pipelines to caching and data access patterns</span></span></p></li><li><p><span style="font-size:1.1em"><span style="color:#121317">Collaborate closely with engineering and product teams to prototype and deliver production-ready solutions grounded in research</span></span></p></li><li><p><span style="font-size:1.1em"><span style="color:#121317">Translate emerging AI trends and workload patterns into scalable, impactful infrastructure designs</span></span></p></li></ul><p style="min-height: 1.7em;"></p><p><span style="font-size:1.1em"><span style="color:#121317">The </span></span><strong><span style="font-size:1.1em"><span style="color:#121317">targeted annual total compensation</span></span></strong><span style="font-size:1.1em"><span style="color:#121317"> for this position ranges from $127,000 to $225,000 depending on education, experience, and demonstrated expertise.</span></span></p><p style="min-height: 1.7em;"></p>