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Senior Engineer- Artificial Intelligence

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Tucows

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Location:
Canada , Toronto

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

126090.00 - 140100.00 CAD / Year
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Job Description:

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.

Job Responsibility:

  • 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

Requirements:

  • 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
  • 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
  • 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
  • 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)
  • Strong understanding of tool use, function calling, and multi-step reasoning
  • Experience designing LLM evaluation frameworks (e.g., RAGAS, promptfoo)
  • Familiarity with observability tools (LangSmith, Helicone, or similar)
  • Strong skills in logging, metrics, alerting, and cost tracking for AI systems
  • Understanding of prompt injection and jailbreak mitigation techniques
  • Experience with PII detection, redaction, and data minimization
  • Familiarity with guardrails, output validation, and content filtering
  • Awareness of AI governance and auditability best practices
  • Experience with cloud-native deployment (preferably AWS)
  • Familiarity with Kubernetes / EKS
  • Understanding of GPU inference optimization (quantization, batching, memory trade-offs)
  • Proven experience mentoring and elevating engineering teams
  • Ability to lead ambiguous, complex projects with minimal oversight
  • Strong communication skills across technical and non-technical audiences
  • Practical, delivery-focused mindset with active engagement in the AI ecosystem
What we offer:
  • Generous benefits
  • Fair compensation
  • Remote-first work for majority of roles
  • Reasonable accommodation for individuals with disabilities

Additional Information:

Job Posted:
April 22, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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