Huawei Canada has an immediate permanent opening for a Technical VP.About the job:- Define the technology roadmap for next-generation data storage and AI retrieval systems, aligning with global R&D and business objectives. Set the global research agenda for AI Data Platforms, with a specific focus on vector-native data lakes, intelligent caching layers, and high-performance retrieval infrastructures that power Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
- Lead the lab's transition to Data-Centric AI, pioneering research in Agent memory system, Knowledge Base, and RAG-optimized data intelligence systems. Drive innovation in dynamic data indexing, hybrid search (semantic + keyword), chunking/parsing strategies, and real-time context freshness-ensuring our storage architectures evolve to handle the unique throughput, latency and accuracy demands at petabyte scale.
- Serve as both Architect and Evangelist, shaping the technical roadmap while maintaining hands-on involvement in critical projects. Lead architecture reviews and performance optimizations for end-to-end AI Data Platform, from unstructured data ingestion and metadata enrichment to vector database sharding and reranking strategies. Prototype next-gen architectures that unify file storage, data lakes, and low-latency vector indexes into a cohesive, AI-ready data stack.
- Lead a world-class research lab, mentoring top-tier engineers and researchers in the specialized fields of Information Retrieval (IR), AI Model, Data Lake, and retrieval mechanisms. Foster a culture of innovation and collaboration focused on solving the challenges for enterprise AI.
- Shape industry standards by publishing influential research on Agent Memory, Knowledge Base, RAG, patenting novel approaches, and representing the company in top-tier tech forums (e.g., VLDB, SIGIR, NeurIPS) to define the future of AI-native data management.
About the ideal candidate: - 5+ years' work experience in data systems research/engineering, with 2+ years in a technical leadership role, specifically focused on data infrastructure for AI/ML workloads.
- Proven track record of delivering industry-leading research and pioneering work in data management, unstructured data processing, scalable storage systems, or AI/ML scalability-with demonstrable experience in Data Lake (e.g., Databricks, Snowflake), information retrieval systems (e.g., Milvus, Pinecone, Cohere), or LLM context engineering.
- Extensive hands-on experience and deep expertise in data storage architectures (specifically object stores and distributed file systems) OR AI/ML infrastructure.
- Deep technical fluency in the challenges of AI Data Platform: including hybrid search tuning, index freshness, multi-tenancy in vector spaces, and cost/latency trade-offs between dense and sparse retrieval methods.
- Exceptional communication skills-able to articulate complex concepts regarding data lifecycle management for Agent and LLMs to executives, and dive into the granular details of technology metrics with engineers.
- Passion for mentoring leaders and fostering innovation in the rapidly evolving intersection of database systems and Generative AI.
Additional Information:All applications for this position are reviewed directly by our hiring team,
we do not use artificial intelligence tools to screen or select candidates.
