Application Deadline: 09/29/2026 Address: 33 Dundas Street West Job Family Group: Technology Hybrid Work Model BMO is building the platform capabilities that make enterprise AI secure, governed, and scalable. We are seeking experienced Senior Engineers to help build and operate the core infrastructure that governs how AI runs at BMO: the AI Gateway, Policy Engine, Identity Fabric, AI Registry, Guardrails Runtime, and AI Observability. This is a build-and-run engineering role. You will design, implement, and operate significant components of these platform capabilities; writing production code, building integrations, and helping run what you. You will not build the AI models or applications themselves (those are domain-owned); you help build the governed platform they run on and the runtime evidence that proves they run within policy, across AWS, Azure, and Microsoft AI surfaces, under OSFI and OCC expectations. You are a hands-on engineer with a strong production track record who takes ownership of your components, cares about operability and correctness, and collaborates well within your team. You work within technical direction and standards set by the team's Principal Engineers and Leads, contribute to design discussions, and mentor more junior engineers. You are energized by hardening and scaling real engineering assets; an existing developer portal, an AI registry, a body of policy-as-code, and gateway integrations into enterprise-grade capabilities.



What You'll Build & Operate Enterprise AI Control Plane Portal & Registry: features of the AI Registry (agents, models, tools, channels, evaluations), self-service onboarding flows, and lifecycle workflows; integrations with external registries. Policy Engine: components of the policy-as-code infrastructure (Cedar/OPA), the compilation pipeline, GitOps-based distribution, and the policy simulation sandbox. Observability & Audit: telemetry pipeline components, OpenTelemetry GenAI instrumentation, trace correlation, and audit-lake ingestion supporting regulator-ready evidence. Governance & Lifecycle: certification workflow components, compliance-scoring automation, and evidence-generation tooling. AI Domain Orchestration Gateway Runtime: components of the inline enforcement engine: request-time policy evaluation, routing, residency, budget/quota, and circuit breaking, built to strict latency budgets; domain-hub deployment across AWS and Azure. Guardrails Runtime: stages of the safety pipeline (input moderation, prompt-injection defense, PII, output validation, hallucination detection, policy enforcement), including bilingual EN/FR support. Identity Fabric: components of workload identity for AI (SPIFFE/SPIRE), token-exchange flows, trust-boundary configuration, Entra Agent ID integration, and cross-cloud token federation. Note on scope: Two of these platforms (Identity Fabric, Policy Engine) are built with AI as the incubation context but are designed to transition to

📌 Senior Artificial Intelligence Platform Engineer & Fabrics (Toronto)
🏢 Bank of Montreal
📍 Toronto