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Open Source Project Maintainer Jobs in Toronto, ON

ShyftLabs

AI Engineer Intern

Toronto, ON · Hybrid

CA$20 - CA$30/hr

Contributions to open-source AI projects, research, hackathons, or technically strong personal projects. Hourly Pay * $20 - $30/Hr (CAD) Why You'll Love Working at ShyftLabs At ShyftLabs, your work ...

NexHealth

Senior Software Engineer

Toronto, ON · On-site +1

Build and maintain bidirectional, real-time integrations with dozens of EHRs, scaling to hundreds ... and related open source projects, including the Kubernetes ecosystem, AWS, and PostgreSQL.

Databricks

Solutions Architect

Toronto, ON · On-site

Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars. What we look ...

Ritchie Bros.

Software Engineer

Mississauga, ON · On-site

You will work closely with senior engineers to develop and maintain applications. We believe in ... Contributions to open-source projects. * Participation in hackathons or coding challenges. IAA ...

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All JobsOpen Source Project Maintainer JobsOpen Source Project Maintainer Jobs in Toronto, ON

Director of AI Engineering - Generative AI & Autonomous Systems (10033) Toronto, Canada

Toronto, ON • On-site

Extreme Networks
Software Development • 1 - 5K employees
Learn more about Extreme Networksexternal

Full-time

Re-posted 23 days ago

Job description

Introduction 
At our Extreme, we create effortless networking experiences that empower people and organizations to advance. We are seeking a Director of AI Engineering to lead the design, development, and delivery of our next-generation AI-native systems. 
This role requires a proven leader who combines technical depth with organizational vision. You will not only set the direction for AI strategy but also ensure that ideas move from research to scalable, production-ready deployments. Your leadership will drive the successful launch of enterprise-grade AI solutions that transform network design, optimization, security, and support. 
Key Responsibilities
  •  
Leadership & Vision 
  • Define the AI engineering vision and long-term roadmap; ensure alignment with business strategy and customer outcomes. 
  • Build, inspire, and scale a world-class AI engineering team, cultivating a culture of innovation, collaboration, and execution. 
  • Mentor senior engineers and emerging leaders, raising the technical and leadership bar across the organization. 
  • Champion responsible AI practices and set quality standards for reliability, ethics, and compliance. 
 
End-to-End Productization 
 
  • Drive the full lifecycle of AI systems: from research exploration and prototyping through enterprise-scale production launches. 
  • Ensure seamless integration of AI into core products, balancing cutting-edge innovation with pragmatic delivery. 
  • Establish and enforce best practices for deployment, monitoring, and lifecycle management of AI systems in production. 
  • Measure impact and ensure that AI solutions deliver tangible business value. 
 
Technical Leadership 
 
  • Provide architectural direction for scalable AI systems leveraging LLMs, multi-agent systems, and generative models. 
  • Guide technical decisions, ensuring systems are reliable, secure, and cloud-native. 
  • Evaluate emerging technologies and frameworks; make informed adoption decisions that strengthen competitive differentiation. 
  • Maintain enough hands-on involvement to earn respect from engineers, while staying focused on strategic leadership. 
 
Cross-Functional & External Influence 
 
  • Partner with product management, engineering, and network experts to define and deliver AI-driven features. 
  • Communicate strategy, progress, and impact to executives, customers, and partners with clarity and influence. 
  • Represent the company externally as a thought leader in AI, contributing to industry forums, open-source communities, and customer engagements. 
Qualifications
  • A degree in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience). 
  • Proven leadership track record: 12+ years in AI/ML engineering, including 5+ years in senior leadership roles managing teams and large-scale initiatives. 
  • End-to-end product launch expertise: Demonstrated success leading AI initiatives from concept through production deployment and adoption at enterprise scale. 
  • Strategic leadership: Ability to define AI roadmaps, prioritize investments, and align execution with business outcomes. 
  • Team builder & mentor: Experience scaling teams, developing leaders, and creating a culture of technical excellence. 
  • Technical credibility: Strong foundation in ML/AI with applied expertise in generative AI, LLMs, RAG, or multi-agent systems; able to guide architecture and evaluate tradeoffs. 
  • Enterprise-scale delivery: Experience integrating AI into production systems with cloud-native architectures (AWS, Azure, GCP). 
  • Influence & communication: Exceptional ability to engage executives, engineers, and customers with clarity and impact. 
Nice to Have:
  • Experience with AI/LLMOps platforms, orchestration frameworks, and lifecycle management. 
  • Domain knowledge in networking, SD-WAN, or observability. 
  • Recognized contributions to the AI ecosystem (open-source projects, patents, or industry thought leadership). 
  • Partnerships with academia, startups, or AI vendors to accelerate innovation. 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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