Principal Engineer - Vector Database

Huawei Canada has an immediate permanent opening for a Principal Engineer.

About the team:

The Distributed Data Storage and Management Lab leads research in distributed data systems, aiming to develop next-generation cloud serverless products that encompass core infrastructure and databases. This lab addresses various data challenges, including cloud-native disaggregated databases, pay-by-query user models, and optimizing low-level data transfers via RDMA. Teams within this lab create advanced cloud serverless data infrastructure and implement cutting-edge networking technologies for Huawei's global AI infrastructure.

About the job:

• Architecting and develop frameworks and engines for next-generation serverless computing tailored to AI workloads (LLM training/inference, agent execution, RL training, etc.).
• Lead the design and innovation of vector database storage engines within a large-scale Data + AI infrastructure platform.
• Drive breakthroughs in vector indexing, retrieval algorithms, and storage architectures, enabling low-latency, high-throughput vector search at scale.
• Define and evolve the technical roadmap for next-generation vector database storage technologies.
• Stay deeply engaged with industry trends, open-source ecosystems, and competitive landscapes; translate customer requirements and real-world workloads into differentiated technical solutions.
• Architect and build high-performance, scalable, and reliable vector storage systems used in production environments.

About the ideal candidate:

• Proven ability to explore, design, and plan innovative systems technologies, with strong technical judgment and architectural thinking.
• Deep understanding of database systems, storage engines, and vector search technologies, with hands-on experience designing and shipping production systems.
• Lead the development of mission-critical products or subsystems, with successful delivery and commercial deployment.
• Strong record of high-quality system design and execution, including component abstraction, modular architecture, and long-term maintainability.
• Experience operating at Staff / Principal / Architect level, influencing technical direction across teams or organizations.
• Experience with vector databases (e.g., FAISS, Milvus, HNSW-based systems, or custom implementations).
• Background in distributed systems, storage systems, or AI infrastructure.
• Contributions to open-source projects or published systems research.