AI Engineer
CA$120,000 – CA$160,000 / yr base salary
Posted 21 Apr 2026
Advertised as “Senior AI Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- People management
- Employment
- Hybrid
- Contract
- Full-time
| Base salary | CA$120,000 – CA$160,000 / yr |
|---|
Field of studyArtificial Intelligence, Computer Science, Data Science (or related)
Study levelBachelor's
About ShyftLabs
At ShyftLabs, we live and breathe data. Since 2020, we've been helping Fortune 500 companies unlock growth with cutting-edge digital solutions that transform industries and create measurable business impact. We're scaling globally with entities in Canada, the U.S., and India and we're looking for passionate problem-solvers who are ready to turn big ideas into real outcomes.
The Opportunity
ShyftLabs is looking for a Senior AI Engineer to sit at the intersection of AI/ML engineering and backend platform development. This isn't a research role, it's a hands-on engineering position where you'll design, build, and ship AI-powered features directly into production systems. You'll work closely with Product, Architecture, and cross-functional engineering teams to integrate intelligent capabilities into our next generation of data-driven platforms, while also contributing to the scalable backend infrastructure that powers them.
The ideal candidate combines deep AI/ML engineering experience with strong backend development skills, someone equally comfortable fine-tuning an LLM integration as they are designing a robust API or event-driven service.
What You'll Do
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Architect and implement AI-powered features end-to-end, from model integration and prompt engineering to deployment, monitoring, and iteration
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Integrate LLM APIs, ML models, and intelligent automation pipelines into scalable, production-grade backend systems
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Fine-tune and optimize models for performance, reliability, and cost efficiency in live environments
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Design and build robust APIs, event-driven services, and third-party integrations that support AI-enabled workflows
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Collaborate with Product to translate business requirements into technical AI solutions, defining scope, complexity, and dependencies
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Build and maintain data pipelines and MLOps workflows to support model deployment and lifecycle management
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Contribute to system architecture decisions, integration patterns, and reusable AI frameworks across the platform
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Partner with data scientists and engineers to ensure smooth, scalable model deployments
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Produce clear technical documentation, architecture diagrams, data flows, API specs, and AI integration patterns
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Lead code reviews, enforce best practices in code quality and testing, and mentor engineers across teams
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Troubleshoot complex production issues across distributed and AI-integrated systems