Ingénieur principal, Opérations de plateforme et observabilité /Senior Engineer, Platform Operations & Observability
Sep 15, 2026McKesson
Saint-Laurent, QC
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Tali AI
Application instructions are available to Premium subscribers.
Role is building an AI platform for clinical workflows with integrations to health records, clinical software, real-time audio pipelines, AI agents, and privacy/compliance — core eHealth/health informatics work.
Tali AI is one of the fastest growing startups in Canada with the mission to use AI and make healthcare more accessible. We are building the AI platform for clinical workflows: automating data collection, processing, and sharing in healthcare, so clinicians can focus on actual care. Our platform is used by thousands of clinicians in Canada and the US, operating across dozens of specialties and deeply integrated with the fragmented landscape of North American health records systems. The technical north star is an operating system for clinical workflows: a platform that healthcare teams configure to automate their data work.
The hard problems are genuinely hard:
We're moving fast in a market that rewards speed, and operating in a domain where breaking clinician trust is not recoverable.
We're hiring a Staff Engineer who reports to the VP Engineering and works on our highest-stakes, most ambiguous technical problems. This is an execution role. You lead through your output, your judgment, and the quality of the standards you set.
You'll work on projects that are strategically critical and don't yet have a clear shape. You give them shape. You de-risk them, make the irreversible decisions visible, and drive them to completion. Our engineering spans:
And you operate across whichever of these a given problem touches. You'll work with a small and growing team that ships daily, reasons clearly, and cares about the clinicians and patients on the other side of every decision.
AI is central to how you work, not as a productivity tool but as a lever for judgment and scope. You use it to take on problems that would otherwise require a team, and you build the architectural foundations (specs, conventions, standards) that let others on the team do the same. When you leave a problem, it's in better shape technically and the team is better equipped to handle the next one.