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Senior Engineer- Artificial Intelligence

1 day ago
Canada
Full-time
Senior
AI Engineer
Software Development
AWS CI/CD Go Kafka Kubernetes LLM PostgreSQL Python RabbitMQ Solid.js TDD
Apply Now
Tucows

Tucows

Tucows, a tech company since 1993, offers domain name services, fiber internet, and SaaS to keep people connected and improve the Internet experience.

Diversified Telecommunication Services
251-1K
Founded 1993
View All Jobs 9

Description

  • 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 attention to scalability, reliability, and cost efficiency.
  • Integrate and fine-tune open-source models and guide model selection and serving strategies.
  • Research emerging AI technologies and align them with product vision.
  • Define and uphold architectural best practices through design and code reviews.
  • Mentor junior and intermediate engineers and provide 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 a 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, including SOLID, DRY, CQRS, Saga, and event-driven design.
  • Deep understanding of the software development life cycle (SDLC).
  • Proven experience building distributed, highly available systems at scale.
  • Strong system design expertise covering APIs, async processing, backpressure, and fault tolerance.
  • Experience with event-driven systems such as Kafka and RabbitMQ.
  • Strong engineering practices, including 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 such as LLaMA, Mistral, and Mixtral.
  • Experience using tools like Ollama and Hugging Face Transformers.
  • Familiarity with fine-tuning techniques such as LoRA, QLoRA, and PEFT.
  • Advanced prompt engineering experience, including few-shot prompting, chain-of-thought, and structured outputs.
  • Expertise in model serving techniques such as batching, async pipelines, caching, and context optimization.
  • Experience designing RAG pipelines end to end.
  • Hands-on experience with vector databases such as pgvector, Pinecone, and 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 such as LangChain and LangGraph.
  • Strong understanding of tool use, function calling, and multi-step reasoning.
  • Experience designing LLM evaluation frameworks such as RAGAS and promptfoo.
  • Familiarity with observability tools such as LangSmith and 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 and EKS.
  • Understanding of GPU inference optimization, including quantization, batching, and 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.

Benefits

  • Base salary range of $126,090 to $140,100 CAD for Canadian residents.
  • Total rewards package with fair compensation and generous benefits.
  • Remote-first culture for most roles, with flexible work from anywhere you have internet access.
  • Hybrid work model for this role, with 3 days per week in the Toronto office.
  • Reasonable accommodation available for candidates and employees with disabilities.
  • Commitment to inclusion and diversity across a wide range of backgrounds and identities.
  • Participation in the E-verify program for all US employees.

Interested in this position?

Apply directly on the company website

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