Principal Engineer, AI Platform
BMO Financial Group2 hours ago
Toronto, CanadaStaff+
Base Salary
$103k - $192k/yr
Responsibilities
- Own AI platform capabilities end to end, including design, implementation, testing, production deployment, and on-call operations.
- Build and operate AI gateways, policy engines, identity fabric, registries, guardrails runtimes, observability pipelines, and audit systems.
- Engineer for operability through instrumentation, SLOs, latency budgets, resilience patterns, failure-mode handling, and runtime evidence.
- Build APIs, interfaces, and integrations consumed by application domains, DevOps pipelines, and enterprise systems.
- Implement policy enforcement, guardrails, identity attestation, auditability, lineage, and compliance evidence for AI workloads.
- Assess emerging AI infrastructure, foundation-model access patterns, and standards while making cost-aware engineering decisions.
- Mentor engineers, review designs and code, set engineering standards, and collaborate with developer experience, security, SDLC, architecture, and domain teams.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline; a Master’s degree is preferred.
- 8+ years of software or platform engineering experience for the Principal level, or 5+ years for the Senior level.
- Experience building and operating shared platform services and production infrastructure at enterprise scale with SLOs and on-call ownership.
- Strong distributed-systems and platform-engineering fundamentals, including latency-sensitive paths, resilience, multi-tenancy, and high availability.
- Strong programming skills in Python and/or Go; TypeScript and Java are assets.
- Experience with cloud-native architecture across AWS and Azure, including containers, Kubernetes, service mesh, and infrastructure as code.
- Experience with robust CI/CD, GitOps, DevSecOps, Git-based workflows, Jira, and Confluence.
- Depth in one or more areas including API gateways, policy-as-code and authorization, workload identity and zero trust, observability and telemetry, or audit and compliance data platforms.
- Working knowledge of GenAI platform patterns, including AI gateways, RAG, agentic patterns, foundation models, embeddings, and guardrails.
- Familiarity with Bedrock, Azure OpenAI, SageMaker, MLflow, LangChain, and LlamaIndex, plus responsible AI, data governance, privacy, cloud security, and IAM.
- Preferred certifications include AWS Certified Solutions Architect, AWS Certified Machine Learning Specialty, Microsoft Certified Azure Solutions Architect Expert, Azure AI Engineer Associate, CKA, CKAD, HashiCorp Terraform Associate, and relevant security or identity certifications.
- Strong communication, analytical, problem-solving, collaboration, self-direction, and delivery skills in an evolving environment.
Benefits
- Health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans.
- Training, coaching, manager support, and network-building opportunities.
- The role participates in an on-call rotation for owned services.
- Application deadline: October 29, 2026.
Tech Stack