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Sr Analyst, DevOps

Job in Toronto, Ontario, C6A, Canada
Listing for: Brookfield Asset Management
Full Time position
Listed on 2026-09-24
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Data Engineering
Salary/Wage Range or Industry Benchmark: 105000 - 120000 CAD Yearly CAD 105000.00 120000.00 YEAR
Job Description & How to Apply Below

Location

Brookfield Place - 181 Bay Street

Technology Services

Technology Services (TS) is responsible for delivering all enterprise infrastructure, applications and related end user technology services across all Brookfield business groups.

Brookfield Culture

Brookfield has a unique and dynamic culture. We seek team members who have a long-term focus and whose values align with our Attributes of a Brookfield Leader:
Entrepreneurial, Collaborative and Disciplined. Brookfield is committed to the development of our people through challenging work assignments and exposure to diverse businesses.

Job Description

The Senior AI Cloud Developer Analyst within Brookfield’s Technical Service Group (TSG) builds and delivers AI solutions from prototype to production, implementing scalable, secure and reliable AI capabilities that meet business needs across the Brookfield environment. This role translates early-stage concepts and prototypes into production-ready systems, working closely with cross-functional technology teams.

Key Responsibilities
  • Implement and scale AI capabilities across projects using AWS & Azure native services, building and maintaining the appropriate AI infrastructure and security controls required to run AI applications reliably in the production environment.

  • Translate prototype and concepts into production-ready implementations by building modular services, APIs, data flows and integration patterns following and applying reusable patterns and enterprise standards.

  • Implement AI features using LLMs, agent frameworks, retrieval-augmented generation, APIs, orchestration tools and enterprise platforms.

  • Integrate AI solutions with Brookfield systems and infrastructure to ensure enterprise-wide interoperability.

  • Build reliable, scalable data pipelines to ingest, transform & validate data – ensuring quality & availability for AI training, inferencing and production workflows

  • Build reusable APIs and integration layers that enable AI capabilities to be consumed across applications.

  • Manage the operational support of AI solutions including deployment, configuration and observability across Brookfield environments.

  • Work closely with internal Brookfield technology teams including cybersecurity, cloud, data, application & project teams to translate requirements into working solutions.

  • Test AI models, APIs, frameworks and platforms for accuracy, latency, cost, scalability, integration fit and operational readiness.

  • Document implementation details, APIs, dependencies, deployment steps, operational procedures and known limitations.

Key Deliverables
  • Deployed, tested and enterprise-integrated AI services, APIs and solutions validated for reliability, security and performance.

  • Validated, documented data pipelines supporting AI training, inference and production workflows.

  • Connectors, API contracts and integration layers linking AI capabilities to business applications.

  • Reusable service templates and implementation patterns adopted across AI projects

  • CI/CD workflows for AI models and service deployments across all environments.

  • Monitoring and observability setup through dashboards, alerts and logging for AI workloads closely monitoring performance, costs and reliability.

  • Hardened AWS and Azure infrastructure and security configurations for AI workloads.

  • Evaluation reports benchmarking AI models, APIs and frameworks for accuracy, latency, costs and scalability.

  • Architecture-aligned technical documentation, including API references, deployment runbooks and known limitations

  • Operational runbooks for incident response, troubleshooting and maintenance of AI workloads.

Required Experience
  • 3-5+ years in software engineering, data engineering or ML engineering roles

  • Hands-on experience building and deploying AI/ML solutions in…

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