Senior Engineer- Artificial Intelligence

About the Opportunity

At Tucows, we have spent three decades building the software and infrastructure that keeps the internet running. We believe in an internet that is open, reliable, and simple. As we integrate Artificial Intelligence into our ecosystem, we aren't looking for superficial implementations; we are looking to build robust, agentic systems that fundamentally improve how millions of users manage their digital identities and connectivity.

We are seeking a Senior AI Engineer to join a dedicated team of engineers building the next generation of intelligent agents that help scale our business. You will bridge the gap between cutting-edge LLM research and production-grade software engineering, leading the development of systems that automate complex tasks with the same reliability our infrastructure is known for.

This is a remote opportunity for applicants in Canada or USA.

What You’ll Do

• System Architecture: Design and implement scalable AI-driven features with a focus on multi-agent systems and advanced RAG architectures.
• Production Excellence: Move beyond the prototype. You will own the full lifecycle of AI services, from model selection and deployment to monitoring in a Kubernetes environment
• Polyglot Engineering: Write clean, maintainable code primarily in Python, while collaborating on core infrastructure services written in Go.
• Ethical AI Leadership: Establish clear standards for data privacy, model bias, and security, including practices like model cards, red-teaming protocols, and privacy impact assessments, ensuring our AI initiatives remain transparent and aligned with our commitment to user trust.

Key Skills & Experience

• Experience: 5+ years of professional software engineering experience, with a proven track record of shipping production-ready applications.
• AI Specialization: Demonstrated expertise working with Large Language Models (LLMs) and agentic frameworks, with a solid understanding of how to apply them to real-world production systems.
• Technical Stack: Advanced proficiency in Python is required. Hands-on experience with Go, or a demonstrated ability to ramp quickly in a Go-heavy environment, is strongly preferred.
• Infrastructure Knowledge: Familiarity with modern DevOps practices, including CI/CD, Docker, and cloud-based inference pipelines on AWS.
• Communication: Exceptional ability to translate complex AI concepts into clear, actionable language for both technical and non-technical audiences.