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BMO
Senior Azure Cloud AI EngineerBMO • Toronto, ON, CAN
Senior Azure Cloud AI Engineer

Senior Azure Cloud AI Engineer

BMO • Toronto, ON, CAN
30+ days ago
Salary
CA$82,800.00 yearly
Job type
  • Full-time
  • Part-time
Job description

About the Role

As a Senior Azure Cloud AI Engineer, you will play a hands‑on senior engineering role within BMO’s Azure cloud and Applied AI ecosystem. You will be responsible for designing, building, and operating secure, scalable Azure infrastructure and platform services that enable data, AI, and Generative AI workloads at scale.

This role blends deep technical execution with strong cross‑functional collaboration. You will work in agile, cross‑functional pods with cloud engineering, data engineering, AI/ML teams, and security and risk partners to evolve BMO’s Azure cloud services. You will help define and implement AI‑ready Azure architectures and guide teams in adopting cloud‑native and AI‑native patterns while maintaining high standards for security, reliability, and operational excellence.

Key Responsibilities

Cloud Engineering & Platform Delivery

  • Design, build, and operate Azure cloud infrastructure and shared platform services supporting AI, GenAI, data, and digital workloads.

  • Implement and maintain Azure landing zones, subscriptions, networking, identity, and governance.

  • Build cloud‑native solutions using Azure PaaS, containers, and managed services.

  • Ensure platforms meet requirements for scalability, resilience, performance, cost efficiency, and reuse.

  • Apply DevOps and SRE practices, including CI/CD, monitoring, alerting, and operational readiness.

AI & GenAI Platform Enablement

  • Enable AI and Generative AI workloads on Azure through secure, standardized platform capabilities.

  • Support AI experimentation and production workloads using Azure AI services and approved tooling.

  • Implement secure service‑to‑service authentication using managed identities and least‑privilege access.

  • Partner with AI and data teams to operationalize AI solutions with production‑grade non‑functional requirements.

Infrastructure as Code & Automation

  • Design and maintain Infrastructure as Code using Bicep, ARM, Terraform, or CDK‑based frameworks.

  • Create reusable, modular deployment patterns that balance self‑service with governance.

  • Automate environment provisioning, configuration, and policy enforcement across environments.

Security, Governance & Risk

  • Apply security‑by‑design principles across identity, networking, encryption, secrets management, and auditability.

  • Ensure Azure solutions comply with security, privacy, data governance, and regulatory requirements.

  • Support architecture reviews, risk assessments, and audits in partnership with security and risk teams.

  • Design platforms with observability, traceability, and operational controls enabled by default.

Required Technical Skills & Competencies

Core Azure Cloud Engineering (Must-have)

  • Hands‑on experience engineering solutions on Microsoft Azure in large‑scale or regulated environments.

  • Strong understanding of Azure networking, identity, access management, and governance.

  • Experience designing for scalability, reliability, performance, and cost efficiency.

  • Proven ability to troubleshoot and operate production Azure environments.

Infrastructure as Code & DevOps (Must-have)

  • Experience with Infrastructure as Code using Bicep, ARM, Terraform, or similar tools.

  • Experience building and operating CI/CD pipelines for infrastructure and application delivery.

  • Familiarity with IAM models, role definitions, and least‑privilege access patterns.

Cloud‑Native Integration & APIs (Must-have)

  • Experience with Azure API Management or similar API gateway solutions.

  • Understanding of secure service exposure, rate limiting, and API lifecycle management.

AI / GenAI Cloud Enablement (Nice‑to‑Have)

  • Experience enabling AI or Generative AI workloads on Azure from a cloud and platform perspective.

  • Familiarity with Azure AI services and AI‑ready infrastructure patterns.

  • Understanding of secure experimentation and production deployment of AI workloads in regulated environments.

Reliability & Observability (Nice‑to‑Have)

  • Experience implementing monitoring, logging, alerting, and operational dashboards.

  • Familiarity with SRE concepts such as SLIs, SLOs, and resilience patterns.

Qualifications & Experience

  • 4+ years of experience in cloud engineering, platform engineering, or infrastructure roles.

  • Proven experience delivering and operating Azure environments.

  • Experience supporting data, analytics, or AI workloads is a strong asset.

  • Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

Salary:

$82,800.00 - $154,800.00

Pay Type:

SalariedThe above represents BMO Financial Group’s pay range and type.Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: About UsAt BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.To find out more visit us at .BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.
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Senior Azure Cloud AI Engineer • Toronto, ON, CAN

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