Engineer II - AI ML Cloud Platform

Work Location:
Toronto, Ontario, Canada

Hours:
37.5

Line of Business:
Technology Solutions

Pay Details:
$91,200 - $136,800 CAD

This role is temporarily eligible for a pay premium above the posted salary range that is reassessed annually. You are encouraged to have an open dialogue with your recruiter who can provide more specific pay details for this role.

Job Description:

Our passion is to advance the organization by enabling Azure AI and ML capability for the enterprise to solve business problems and deliver TD products faster.

We are looking for an Azure AI / ML Engineer to deliver enterprise data services/capabilities and solutions on Azure. The perfect candidate will have previous AI / ML cloud experience delivering enterprise data solutions within financial services including knowledge of the security and regulatory requirements.

KEY ACCOUNTABILITIES

CUSTOMER

1. Leverage deep technology expertise for own area of specialization to deliver and ensure that all areas across the organization that provision, manage and support various technologies have the necessary tools, processes and documentation required to effectively execute on their respective mandates
2. Execute on Engineering strategy as it relates to the introduction of tools and the automation of build, test, release and configure activities across Application, Platform and Infrastructure
3. Partner with the Operations team to automatically integrate with appropriate tools and processes as part of automated/self-serve Application, Platform or Infrastructure releases
4. Work with partners across Technology and apply in-depth understanding of relevant business needs to identify and leverage synergies across the various areas
5. Act as the expert or lead innovator and agent of change for the programs and services under management
6. Work with other teams to implement best practices for engineering and management
7. Work with vendor platform providers and engineering peers to keep abreast of trends, products, frameworks, and applications
8. Identify and effectively manage stakeholder engagement and impacts across the enterprise
9. Interpret client needs, assess engineering related requirements and identify solutions to non-standard requests

SHAREHOLDER

1. Apply best practices and knowledge of internal / external business issues to improve products or services in own discipline
2. Monitor and control costs within own work
3. May interact with governance and control groups, (e.g. regulatory / operational risk, compliance and audit) to provide subject matter expertise and consult on risk issues / items related to Engineering technology and tools
4. May develop and/or contribute to negotiations of third party contracts/agreements
5. Maintain knowledge and understanding of external development, engineering and emerging solutions, market conditions and their impact
6. Proactively identify emerging technologies and innovative solutions for building more robust platform domains

EMPLOYEE / TEAM

1. Continuously enhance knowledge/expertise in own area and keep current with emerging industry trends, new technologies and best practices in the external market that can contribute to delivering effective client solutions
2. Prioritize and manage own workload in order to deliver quality results and meet timelines
3. Support a positive work environment that promotes service to the business, quality, innovation and teamwork and ensure timely communication of issues/ points of interest
4. Participate in knowledge transfer with senior management, the team, other technical areas and business units
5. Work effectively as a team, supporting other members of the team in achieving business objectives and providing client services
6. Identify and recommend opportunities to enhance productivity, effectiveness and operational efficiency of the business unit and/or team

BREADTH & DEPTH

1. Expert knowledge of specific domain or range of engineering frameworks, technology, tools, processes and procedures, as well as organization issues
2. Expert knowledge of TD applications, systems, networks, innovation, design activities, best practices, business / organization, Bank standards, and may fulfill a governance role
3. Expert knowledge and experience in own discipline; integrates knowledge of business and functional priorities
4. Acts as a key contributor in a complex and critical environment
5. May provide leadership to teams or projects; shares expertise
6. Applies in-depth skills and broad knowledge of the business to address complex problems and non-standard situations
7. Generally reports to a Senior Manager or above
8. Passionate about deep learning and natural language models
9. AIOps/MLOps mindset enabling services and developing pipelines for managing training models and production models.
10. Collaborate with internal application development teams to leverage AI/ML services to solve business objectives
11. Understand security, risks and mitigations to load data and training models securely into Cloud
12. Programming skills with experience in API and Webhook development using Python, Git Actions and Terraform
13. Write and use Azure RM and Terraform templates
14. Understand Azure security features (data protection, authentication, RBAC, etc)
15. Understanding of Public Key Infrastructure (PKI), handling public key and private key certificates in Azure environment for Paas services and applications
16. Ability to troubleshoot Azure, DNS, Azure connectivity, NSG, routing
17. Proficiency in cloud automation using native Azure CLI
18. Understand concepts related to deploying platform and data analytics via CI/CD pipeline
19. Ensure that all cloud solutions follow internally defined security and compliance controls
20. Develop/Consume APIs, SDKs and Webhook for multi-directional integration of cloud orchestration platform with enterprise systems, DevOps Tools and cloud platforms
21. Ability to participate in fast-paced DevOps Engineering teams within Scrum agile processes
22. A critical thinker with strong research and analytics skills
23. Self-motivated with a positive attitude and an ability to work independently and in a team

EXPERIENCE & EDUCATION

1. University or post-graduate degree
2. Strong academic background (e.g., computer science, engineering)
3. 7 + years relevant experience
4. 3+ years AI and ML platform engineer
5. 5+ years of experience developing platform orchestration code in Azure Python SDK, Terraform and GitHub Runners
6. Strong expertise with delivering Cloud Infrastructure As Code (IAC) leveraging CI/CD pipelines, Terraform and Git Actions.
7. Demonstrated knowledge of cloud provisioning and administration, cloud bursting, cloud interoperability, cloud disaster recovery and business continuity strategies, as well as performance measurement and monitoring in the cloud
8. Must be a self-starter, demonstrated ability to take independent action to achieve results.
9. Highly developed critical thinking, analytical and problem solving skills