Research Engineer - Agentic Software Systems Engineering

Huawei Technologies Canada Co., Ltd.•Markham, ON

4d•CA$127,000 - CA$225,000

About The Position

Huawei Canada has an immediate permanent opening for a Research Engineer within the Intelligent Complex Systems Team, part of the Waterloo Research Centre. This team focuses on recent advancements in artificial intelligence (AI) and robotics for broader applications, researching AI challenges such as matching human capabilities and ensuring the safety of collaborative AI systems. The role involves researching, prototyping, and building a complete agentic software system engineering framework. This framework will span the foundation model layer, the code agent tooling layer, and the upper-layer system engineering framework, aiming to enable AI agents to evolve from consumer assistants into full-fledged software engineering collaborators. The position will investigate how code agents are reshaping software engineering paradigms and design new paradigms for human-Code Agent collaborative development, including task decomposition and role allocation. It also includes researching multi-agent collaboration patterns for software engineering, developing systematic techniques for coordination, decision-making, and execution across specialized agents for repository-scale and product-scale tasks. Additionally, the role requires building and optimizing full-stack engineering capabilities and reusable assets for code agents, and contributing to the incubation of end-to-end code agent products powered by multi-agent systems.

Requirements

A PhD degree in Computer Science, Software Engineering, Requirements Engineering, Artificial Intelligence or closely related fields.
Hands-on experience with modern code agent tools framework and familiarity with system engineering methodologies in the agentic coding space, with a solid understanding of how foundation models, agent tooling, and engineering frameworks interact across the full stack.
Strong background in AI software development system workflow design and multi-agent systems for software engineering, with experience decomposing complex development tasks into agent-executable steps and defining coordination protocols, role specialization, and decision-making across planning, coding, reviewing, testing, and debugging agents.
Experience developing reusable engineering assets and evaluation frameworks for code agents —including sub-agents, skills, tool libraries, prompt/context engineering modules, and benchmarking pipelines on realistic software engineering scenarios—to improve agent capability, reliability, and human-collaboration quality.
Proficiency in Python (or TypeScript, Go, or C/C++), with the ability to translate research ideas into scalable, reproducible prototype systems and to communicate technical insights effectively across research, engineering, and product teams.

Nice To Haves

Publications at top-tier venues (e.g., ICSE, FSE, NeurIPS, ICML, ICLR, ACL) or significant open-source contributions to code agent frameworks or agentic systems are highly valued.

Responsibilities

Research, prototype, and build a complete agentic software system engineering framework spanning the foundation model layer, the code agent tooling layer, and the upper-layer system engineering framework, enabling AI agents to evolve from consumer assistants into full-fledged software engineering collaborators.
Investigate how the rise of code agents is reshaping software engineering paradigms, and design new paradigms for human–Code Agent collaborative development, including the engineering decomposition of complex software development tasks and effective role allocation between humans and agents.
Research multi-agent collaboration patterns for software engineering, developing systematic techniques for coordination, decision-making, and execution across specialized agents (planning, coding, reviewing, testing, debugging) on repository-scale and product-scale tasks.
Build and optimize full-stack engineering capabilities and reusable assets for code agents—including sub-agents, skills, tool libraries, prompt/context engineering modules, and workflow templates—and contribute to the incubation of end-to-end code agent products powered by multi-agent systems.