LocationBrookfield Place - 181 Bay StreetTechnology ServicesTechnology Services (TS) is responsible for delivering all enterprise infrastructure, applications and related end user technology services across all Brookfield business groups.Brookfield CultureBrookfield 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 DescriptionThe 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.<h2></h2><h2>Key Responsibilities</h2><ul><li>Implement and scale AI capabilities across projects using AWS &amp; Azure native services, building and maintaining the appropriate AI infrastructure and security controls required to run AI applications reliably in the production environment.</li><li>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.</li><li>Implement AI features using LLMs, agent frameworks, retrieval-augmented generation, APIs, orchestration tools and enterprise platforms.</li><li>Integrate AI solutions with Brookfield systems and infrastructure to ensure enterprise-wide interoperability.</li><li>Build reliable, scalable data pipelines to ingest, transform &amp; validate data – ensuring quality &amp; availability for AI training, inferencing and production workflows</li><li>Build reusable APIs and integration layers that enable AI capabilities to be consumed across applications.</li><li>Manage the operational support of AI solutions including deployment, configuration and observability across Brookfield environments.</li><li>Work closely with internal Brookfield technology teams including cybersecurity, cloud, data, application &amp; project teams to translate requirements into working solutions.</li><li>Test AI models, APIs, frameworks and platforms for accuracy, latency, cost, scalability, integration fit and operational readiness.</li><li>Document implementation details, APIs, dependencies, deployment steps, operational procedures and known limitations.</li></ul><h2>Key Deliverables</h2><ul><li>Deployed, tested and enterprise-integrated AI services, APIs and solutions validated for reliability, security and performance.</li><li>Validated, documented data pipelines supporting AI training, inference and production workflows.</li><li>Connectors, API contracts and integration layers linking AI capabilities to business applications.</li><li>Reusable service templates and implementation patterns adopted across AI projects</li><li>CI/CD workflows for AI models and service deployments across all environments.</li><li>Monitoring and observability setup through dashboards, alerts and logging for AI workloads closely monitoring performance, costs and reliability.</li><li>Hardened AWS and Azure infrastructure and security configurations for AI workloads.</li><li>Evaluation reports benchmarking AI models, APIs and frameworks for accuracy, latency, costs and scalability.</li><li>Architecture-aligned technical documentation, including API references, deployment runbooks and known limitations</li><li>Operational runbooks for incident response, troubleshooting and maintenance of AI workloads.</li></ul><h2>Required Experience</h2><ul><li>3-5+ years in software engineering, data engineering or ML engineering roles</li><li>Hands-on experience building and deploying AI/ML solutions in production environments (not just POCs/notebooks)</li><li>Experience translating prototypes or proof-of-concepts into scalable production-grade AI based solutions</li><li>Working experience with AWS and/or Azure, particularly AI/ML services (e.g., SageMaker, Bedrock, Azure ML, Azure Foundry)</li><li>Experience with IAM, networking &amp; security configuration for cloud workloads.</li><li>Experience with containerization and orchestration (Docker, Kubernetes/ECS/EKS)</li><li>Practical experience with LLMs, prompt engineering and agent orchestration frameworks (e.g. Langchain/LangGraph, MS Agent Framework/Semantic Kernel)</li><li>Experience implementing RAG (retrieval-augmented generation) architectures, including vector databases (Azure AI Search, AWS OpenSearch, Bedrock KB, AWS DocumentDB)</li><li>Familiarity with model serving and inference patterns, including real-time, batch and API based approaches.</li><li>Strong API development experience (REST, GraphQL)</li><li>Proficiency in Python with CI/CD pipeline experience (GitHub Actions, Azure DevOps)</li></ul><h2>Skills &amp; Qualifications</h2><ul><li>Bachelor’s degree in computer science, Software Engineering, Data Science or related field</li><li>Proficiency in Python, with familiarity in JavaScript/TypeScript</li><li>Skilled in LLMs, prompt engineering, RAG architectures, vector databases and agent orchestration frameworks.</li><li>Proficient in REST/GraphQL API build, microservices and integration patterns</li><li>Proficient in building ETL/ELT pipelines and validating data using cloud native tools like AWS Glue or Azure Data Factory</li><li>Proficient in CI/CD pipelines, containerization (Docker, Kubernetes/ECS/EKS), and MLOps practices including model deployment, versioning, and monitoring</li><li>Strong problem solving and analytical thinking with a required ability to translate ambiguous requirements into working solutions</li><li>Effective technical communicator with a required ability to clearly communicate solutions to both technical and non-technical stakeholders</li><li>Demonstrated decisiveness taking ownership of technical decisions and solutions willing to make calculated judgement calls under ambiguity rather than defaulting to indecision.</li><li>Adaptable to work with evolving AI tools/frameworks in a fast-changing landscape</li></ul><h2>Preferred Qualifications</h2><ul><li>AWS Certified Machine Learning Engineer - Associate</li><li>AWS Certified Generative AI Developer - Professional</li><li>Azure AI Cloud Developer Associate</li><li>Azure AI App and Agent Developer Associate</li></ul>Salary Range: C$105K-120KPosition Opening Reason:New Position Brookfield is committed to maintaining a Positive Work Environment that is safe, respectful; our shared success depends on it. We do not tolerate workplace discrimination, violence or harassment. We are proud to be an Equal Opportunity Employer and make employment decisions based on qualifications, merit, and business needs, without regard to any characteristic protected by applicable law. Applicant information is collected and handled in accordance with our Applicant Privacy Notice. As part of this commitment, we provide barrier-free and accessible employment practices in accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and applicable human rights legislation. If you require a Human Rights Code-protected accommodation at any stage of the recruitment process, please let us know when contacted, and we will work with you to meet your needs.

Brookfield is invested in long-life, high-quality assets and businesses around the world that form the backbone of the global economy. With over $925 billion in assets under management, and over 100 years&rsquo; experience as an owner and operator, we put our own capital to work in virtually every transaction, aligning interests with our partners and investors, and bringing the strengths of our operational expertise, global reach and large-scale capital to bear in everything we do.
To learn more about our global businesses spanning renewable power and transition, infrastructure, real estate, private equity and credit, please visit www.brookfield.com.
Phishing and Fraudulent Websites Warning Please be aware of the misuse of the Brookfield name and brand by individuals and groups fraudulently publishing fake websites and engaging in &ldquo;phishing&rdquo; scams that seek personal or confidential information from potential job candidates. This includes the posting of fake Brookfield job offers on LinkedIn and other career sites.

Sr Analyst, DevOps

LocationBrookfield Place - 181 Bay StreetTechnology ServicesTechnology Services (TS) is responsible for delivering all enterprise infrastructure, applications and related end user technology services across all Brookfield business groups.Brookfield CultureBrookfield 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 DescriptionThe 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.<h2></h2><h2>Key Responsibilities</h2><ul><li>Implement and scale AI capabilities across projects using AWS &amp; Azure native services, building and maintaining the appropriate AI infrastructure and security controls required to run AI applications reliably in the production environment.</li><li>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.</li><li>Implement AI features using LLMs, agent frameworks, retrieval-augmented generation, APIs, orchestration tools and enterprise platforms.</li><li>Integrate AI solutions with Brookfield systems and infrastructure to ensure enterprise-wide interoperability.</li><li>Build reliable, scalable data pipelines to ingest, transform &amp; validate data – ensuring quality &amp; availability for AI training, inferencing and production workflows</li><li>Build reusable APIs and integration layers that enable AI capabilities to be consumed across applications.</li><li>Manage the operational support of AI solutions including deployment, configuration and observability across Brookfield environments.</li><li>Work closely with internal Brookfield technology teams including cybersecurity, cloud, data, application &amp; project teams to translate requirements into working solutions.</li><li>Test AI models, APIs, frameworks and platforms for accuracy, latency, cost, scalability, integration fit and operational readiness.</li><li>Document implementation details, APIs, dependencies, deployment steps, operational procedures and known limitations.</li></ul><h2>Key Deliverables</h2><ul><li>Deployed, tested and enterprise-integrated AI services, APIs and solutions validated for reliability, security and performance.</li><li>Validated, documented data pipelines supporting AI training, inference and production workflows.</li><li>Connectors, API contracts and integration layers linking AI capabilities to business applications.</li><li>Reusable service templates and implementation patterns adopted across AI projects</li><li>CI/CD workflows for AI models and service deployments across all environments.</li><li>Monitoring and observability setup through dashboards, alerts and logging for AI workloads closely monitoring performance, costs and reliability.</li><li>Hardened AWS and Azure infrastructure and security configurations for AI workloads.</li><li>Evaluation reports benchmarking AI models, APIs and frameworks for accuracy, latency, costs and scalability.</li><li>Architecture-aligned technical documentation, including API references, deployment runbooks and known limitations</li><li>Operational runbooks for incident response, troubleshooting and maintenance of AI workloads.</li></ul><h2>Required Experience</h2><ul><li>3-5+ years in software engineering, data engineering or ML engineering roles</li><li>Hands-on experience building and deploying AI/ML solutions in production environments (not just POCs/notebooks)</li><li>Experience translating prototypes or proof-of-concepts into scalable production-grade AI based solutions</li><li>Working experience with AWS and/or Azure, particularly AI/ML services (e.g., SageMaker, Bedrock, Azure ML, Azure Foundry)</li><li>Experience with IAM, networking &amp; security configuration for cloud workloads.</li><li>Experience with containerization and orchestration (Docker, Kubernetes/ECS/EKS)</li><li>Practical experience with LLMs, prompt engineering and agent orchestration frameworks (e.g. Langchain/LangGraph, MS Agent Framework/Semantic Kernel)</li><li>Experience implementing RAG (retrieval-augmented generation) architectures, including vector databases (Azure AI Search, AWS OpenSearch, Bedrock KB, AWS DocumentDB)</li><li>Familiarity with model serving and inference patterns, including real-time, batch and API based approaches.</li><li>Strong API development experience (REST, GraphQL)</li><li>Proficiency in Python with CI/CD pipeline experience (GitHub Actions, Azure DevOps)</li></ul><h2>Skills &amp; Qualifications</h2><ul><li>Bachelor’s degree in computer science, Software Engineering, Data Science or related field</li><li>Proficiency in Python, with familiarity in JavaScript/TypeScript</li><li>Skilled in LLMs, prompt engineering, RAG architectures, vector databases and agent orchestration frameworks.</li><li>Proficient in REST/GraphQL API build, microservices and integration patterns</li><li>Proficient in building ETL/ELT pipelines and validating data using cloud native tools like AWS Glue or Azure Data Factory</li><li>Proficient in CI/CD pipelines, containerization (Docker, Kubernetes/ECS/EKS), and MLOps practices including model deployment, versioning, and monitoring</li><li>Strong problem solving and analytical thinking with a required ability to translate ambiguous requirements into working solutions</li><li>Effective technical communicator with a required ability to clearly communicate solutions to both technical and non-technical stakeholders</li><li>Demonstrated decisiveness taking ownership of technical decisions and solutions willing to make calculated judgement calls under ambiguity rather than defaulting to indecision.</li><li>Adaptable to work with evolving AI tools/frameworks in a fast-changing landscape</li></ul><h2>Preferred Qualifications</h2><ul><li>AWS Certified Machine Learning Engineer - Associate</li><li>AWS Certified Generative AI Developer - Professional</li><li>Azure AI Cloud Developer Associate</li><li>Azure AI App and Agent Developer Associate</li></ul>Salary Range: C$105K-120KPosition Opening Reason:New Position Brookfield is committed to maintaining a Positive Work Environment that is safe, respectful; our shared success depends on it. We do not tolerate workplace discrimination, violence or harassment. We are proud to be an Equal Opportunity Employer and make employment decisions based on qualifications, merit, and business needs, without regard to any characteristic protected by applicable law. Applicant information is collected and handled in accordance with our Applicant Privacy Notice. As part of this commitment, we provide barrier-free and accessible employment practices in accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and applicable human rights legislation. If you require a Human Rights Code-protected accommodation at any stage of the recruitment process, please let us know when contacted, and we will work with you to meet your needs.

Sr Analyst, DevOps

About the Job

About the Company

Brookfield Global Asset Management Limited

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