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Technical VP - AI Data Platform

Huawei Technologies Canada Co., Ltd. Open · verified Oct 24, 2026
On-site Markham Full-time VP Data Engineering

At a glance

VP-level Data Engineering role at Huawei Technologies Canada Co., Ltd. Markham · full-time · no salary stated · we estimate CA$156,250–CA$232,338 across Canada.

Estimated pay

Huawei Technologies Canada Co., Ltd. has not published a salary for this role. The figure below is our estimate, not theirs.

CA$156,250 – CA$232,338
What the middle half of lead data engineering roles in Canada paid, among postings that did state a salary.
Worked out from 6 postings that stated pay, median CA$191,500. Last updated Oct 15, 2026.
RoleData Engineering
SeniorityVP
LocationMarkham
WorkplaceOn-site
EmploymentFull-time
PostedJul 18, 2025 · 1y ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Set the direction for storage and AI retrieval research, including vector data lakes, caching and retrieval systems for LLMs and RAG
  • Guide work on agent memory, knowledge bases and RAG-focused data systems as the lab moves toward data-centric AI
  • Improve indexing, hybrid search, data chunking and context freshness to meet storage performance needs at petabyte scale
  • Review platform designs and tune performance from unstructured data intake through metadata enrichment, vector sharding and reranking
  • Build prototypes that bring file storage, data lakes and fast vector indexes together, while mentoring researchers and engineers

What you bring

  • At least five years in data systems research or engineering, including two years in technical leadership focused on AI/ML data infrastructure
  • A record of research or original work in data management, unstructured data processing, scalable storage or AI/ML scalability
  • Deep practical expertise in object storage and distributed file systems, or in AI/ML infrastructure
  • Strong command of hybrid search, index freshness, vector-space multi-tenancy and dense-versus-sparse retrieval trade-offs

Who this fits

This VP role suits a hands-on technical leader who can set research direction, guide engineers and researchers, and work on critical platform projects. You’ll need to communicate technical details to both executives and engineering teams.

From the employer

Huawei Canada has an immediate permanent opening for a Technical VP.

About the team:

The Emerging Storage Lab is a research group based at Huawei Canada's Toronto Research Centre that is focused on next-generation data and storage technologies and innovations. Our team comprises graduate computer engineers and computer scientists with diverse industry experience, ranging from 0 to over 20 years. This lab investigates various data storage-related topics, including data management, data catalog, data fabric, file systems, storage networks, and AI storage, aiming to advance the field and drive data storage technological progress in the new AI era.

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:

Huawei Canada is committed to a fair, inclusive, and accessible recruitment process. If you require accommodation during any stage of the hiring process, please let us know and we will work with you to meet your needs.

All applications for this position are reviewed directly by our hiring team, we do not use artificial intelligence tools to screen or select candidates.

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

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By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.