Researcher - AI Agents & Knowledge Graphs

Huawei Canada; Ottawa; On-site; CAD 90,000 - 140,000; Full time

Job summary

Huawei Canada is seeking a Researcher for a 12-month contract to join our Advanced Optical Technology Lab in Ottawa, Ontario. The role focuses on applying AI, LLMs, and graph-based reasoning to telecom and optical network data, delivering demos and prototypes.

You will collaborate with researchers, develop ontology models, and embed AI components into near-production systems, with a strong emphasis on Python and C/C++.

Qualifications

• Master’s or equivalent in CS/AI; strong project experience accepted for Bachelor’s.

Responsibilities

• Explore applying LLMs, multi-agent systems, ontology reasoning, and knowledge graphs to telecom data.
• Design and evaluate AI agents and LLM-powered workflows for network ops and digital twins.
• Collaborate with researchers to build demos, prototypes, and proof-of-concept systems.
• Develop ontology models, knowledge graphs, and agent tools for real applications.
• Embed AI models into production-grade systems.
• Contribute to research docs and evaluate new AI/ML techniques.

Skills

Python

C/C++

LLMs

Knowledge Graphs

RAG

Documentation

Education

Master’s degree

Bachelor’s degree with strong project experience

Tools

Neo4j

RDF/OWL

SPARQL

Cypher

Ontology tools

Job description

Huawei Canada has an immediate 12-month contract opening for a Researcher.

About the Team

Huawei Canada's Advanced Optical Technology Lab focuses on advanced R&D in high-performance optical communications and networking. Our expert team specializes in transmission algorithms, systems, physics, and optical network management. The lab engages in projects ranging from deep research to developing key product features, actively participating in standards organizations and collaborative research with partners. Our multicultural environment fosters innovation, mentorship, and a passion for learning. If you thrive on solving complex technical challenges, this lab is your ideal place.

About the Job

• Explore the feasibility of applying LLMs, multi-agent systems, ontology-driven reasoning, and knowledge graphs to telecom and optical network data.
• Design, implement, and evaluate AI agents and LLM-powered workflows to solve real-world problems in network operations, self-healing, root-cause analysis, and digital twins.
• Collaborate with researchers and domain experts to build demos, prototypes, and proof-of-concept systems.
• Develop and integrate ontology models, knowledge graph schemas, and agent skills/tools into concrete applications.
• Embed AI models, agents, and data-driven algorithms into production-grade or near-production systems.
• Contribute to research explorations and technical documentation; support the team in evaluating new AI/ML techniques.

The total target annual compensation (based on 2,080 hours per year) ranges from $90,000 to $140,000 depending on education, experience, and demonstrated expertise.

Job requirements

About the ideal candidate

• Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field; Bachelor’s degree candidates with strong relevant project experience will also be considered.
• Strong software engineering skills with solid coding ability in Python, and familiarity with C/C++ or other systems languages.
• Hands‑on experience with LLMs (prompt engineering, fine‑tuning, RAG, agent frameworks) and knowledge graph / ontology technologies (e.g., Neo4j, RDF/OWL, SPARQL, Cypher, or similar).
• Ability to work independently and collaboratively in a research‑oriented R&D environment.
• Optical communication, telecom network, or network automation background is an asset.

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.