Senior Engineer- Artificial Intelligence

Tucows Domains is the world’s largest wholesale domain registrar, responsible for maintaining the health, neutrality, and openness of an important—but largely invisible part of the Internet: the domain name system (DNS).

As part of Tucows—one of the world’s largest Internet companies—Tucows Domains has a rich history of helping make the Internet better, operating globally under the Ascio, Enom, Hover and OpenSRS brands.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet! Today, over one thousand people from over 20 countries are part of our team.

If this sounds exciting to you, join the herd!

About the Opportunity

We’re looking for a seasoned Senior AI Engineer to join our growing AI team. In this role, you’ll take a leading hand in designing and building innovative AI-powered systems that transform how users interact with our domain-related tools and services.

You’ll set technical direction, guide and mentor engineers, and collaborate cross-functionally to prototype, develop, and deploy intelligent solutions using open-source models and modern infrastructure.

Work Model: Hybrid — 3 days per week in our Toronto office.

What You’ll Do

• Lead the architecture and development of AI-driven features using Python and Golang
• Own end-to-end delivery of LLM-based systems — from prototype to production — with a focus on scalability, reliability, and cost efficiency
• Integrate and fine-tune open-source models (e.g., LLaMA, Mistral, Mixtral) and drive model selection and serving strategies
• Research and champion emerging AI technologies aligned with product vision
• Define and uphold architectural best practices through design and code reviews
• Mentor junior and intermediate engineers, providing technical leadership on complex problems
• Translate AI capabilities and constraints into clear business context for non-technical stakeholders
• Shape responsible AI practices, including safety, privacy, and governance
• Stay current with the open-source AI ecosystem and bring forward relevant innovations

Key Skills & Experience

Core Engineering & Software Architecture

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field
• 5+ years of software engineering experience, with recent focus on AI/LLM systems
• Advanced proficiency in Python and Golang
• Strong knowledge of software design patterns (SOLID, DRY, CQRS, Saga, event-driven)
• Deep understanding of the Software Development Life Cycle (SDLC)
• Proven experience building distributed, highly available systems at scale
• Strong system design expertise: APIs, async processing, backpressure, fault tolerance
• Experience with event-driven systems (Kafka, RabbitMQ)
• Strong engineering practices: TDD, CI/CD, code reviews, and technical debt management
• Experience writing and communicating Architecture Decision Records (ADRs)
• Strong knowledge of PostgreSQL, schema design, and query optimization

LLM & AI Application Engineering

• Deep understanding of transformer architectures and inference trade-offs
• Hands-on experience with open-source models (LLaMA, Mistral, Mixtral)
• Experience using tools like Ollama and Hugging Face Transformers
• Familiarity with fine-tuning techniques (LoRA, QLoRA, PEFT)
• Advanced prompt engineering (few-shot, chain-of-thought, structured outputs)
• Expertise in model serving: batching, async pipelines, caching, context optimization

RAG & Knowledge Systems

• Experience designing RAG pipelines end-to-end
• Hands-on experience with vector databases (pgvector, Pinecone, Weaviate)
• Strong understanding of embeddings, chunking, indexing, and re-ranking
• Experience building scalable data pipelines for ingestion and retrieval

Agentic Systems & Tooling

• Experience building multi-agent systems with robust state and failure handling
• Familiarity with Model Context Protocol (MCP) design patterns
• Experience with orchestration frameworks (LangChain, LangGraph)
• Share