Senior Artificial Intelligence Platform Engineer & Fabrics
BMO Financial Group2 hours ago
Toronto, CanadaSenior
Base Salary
$76k - $142k/yr
Responsibilities
- Own and deliver platform components and features through design, implementation, testing, shipping, and production operation.
- Build APIs, MCP servers, integrations, and tooling consumed by domains, DevOps pipelines, and enterprise systems.
- Develop policy engines, identity services, gateways, guardrails, registries, observability, audit, and governance capabilities.
- Build operability into services through metrics, tracing, SLO-aware design, monitoring, and incident response.
- Produce runtime evidence connecting AI activity to policy enforcement, identity, and lineage for regulatory review.
- Participate in on-call for team-operated services and mentor junior engineers.
- Collaborate with Principal Engineers, Leads, AI Developer Experience, AI Security, and AI SDLC teams.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline; a master’s degree is an asset.
- At least 5 years of software or platform engineering experience building and operating production services.
- Experience with production operations, including deployments, monitoring, incident response, and on-call.
- Hands-on depth in at least one of API or gateway services, policy-as-code or authorization, workload identity or security, observability or telemetry, or audit and data platforms.
- Strong software engineering fundamentals, API design skills, and understanding of distributed-system concepts such as latency, resilience, and availability.
- Strong programming skills in Python and/or Go; TypeScript or Java experience is an asset.
- Cloud-native development experience on AWS and/or Azure, including containers, Kubernetes, and infrastructure as code.
- Experience with CI/CD, GitOps, DevSecOps, Git-based workflows, Jira, and Confluence.
- Knowledge of GenAI platform patterns, including LLM or AI gateways, RAG, agentic patterns, embeddings, and guardrails.
- Familiarity with Bedrock, Azure OpenAI, SageMaker, MLflow, LangChain, or LlamaIndex is an asset.
- Awareness of responsible AI, AI and data governance, privacy, cloud security, and IAM for AI workloads.
- Preferred certifications include AWS Certified Solutions Architect, AWS Certified Machine Learning Specialty, Microsoft Certified Azure AI Engineer Associate, or Azure Solutions Architect Expert.
Benefits
- Hybrid work model.
- Health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans.
- Training, coaching, manager support, and network-building opportunities.
- Application deadline is September 29, 2026, with the listed work address at 33 Dundas Street West.
Tech Stack