Address:

Please note this is a hands-on Architect role; hands on coding experience is a must. Hybrid (2 days/week working in office downtown Toronto).

MUST HAVE: Architecture experience, AWS Cloud, production-grade Artificial Intelligence experience, Hands-on experience coding, SDLC, Data Architecture.

• Contributes to AI Adoption and Enterprise Architecture from an AI and Data architecture perspective, while bringing their hands on Engineering skills to align business needs with technologies. Partners with internal stakeholders to define the technology capabilities, principles, standards, and guidelines regarding AI including machine learning and data architecture. Provide expert advice regarding AI and Data architecture in critical programs and initiatives. Validates solution architecture for adherence to defined policies, standards and guidelines including regulatory directives. Partners with broader internal stakeholders to define architectural possibilities and futures. Works with business and development teams to recommend processes or system design enhancements. Ensures that systems are functionally appropriate, technically sound, and well-integrated.  

  • Lead the design of end-to-end AI solution reference architectures, integrating data architecture components such as data pipelines, model training, deployment, and monitoring.

  • Apply innovative AI, data, and analytics technologies to enterprise platforms, aligning technical solutions with complex business and IT requirements.

  • Develop and maintain the technical roadmap for enterprise platform capabilities to realize the organization’s AI and data vision.

  • Support initiatives related to data acquisition, processing, and utilization through the enterprise AI and data platform.

  • Define infrastructure requirements for AI systems; evaluate and select tools, platforms, and frameworks to ensure scalability, performance, and security.

  • Serve as a technical thought leader in AI, machine learning, and data architecture, recognized for deep architectural expertise.

  • Provide strategic advice and guidance to business units on the implementation of AI and data solutions.

  • Ensure project deliverables align with target state architecture and challenge architectural decisions where necessary to uphold governance standards.

  • Identify opportunities to enhance data architecture across diverse and complex business functions and processes.

  • Build and maintain strong relationships with internal stakeholders across enterprise, technology, and business groups to ensure adherence to architecture standards.

  • Monitor industry trends and emerging technologies to inform strategic decisions and recommend relevant innovations.

  • Conduct research and proof-of-concept initiatives to evaluate emerging technologies and recommend their application.

  • Perform additional responsibilities as required to support enterprise goals.

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  Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering.

  • 10+ years of combined experience in software development, data engineering, architecture and Artificial Intelligence.

  • 5 years experience as a Data Architect

  • 2+ years experience delivering AI Architectures in production

  • 3 years experience specific to AWS Cloud

  • Hands on current capability to code (at least with Python)

  • Production-grade experience with AI solutions

  • Experience with GenAI, LLMs, or reinforcement learning in production environments and AI solution delivery.

  • Proven experience architecting and deploying AI/ML solutions

  • Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch), cloud platforms (e.g., Azure, AWS, GCP), and MLOps tools. Preferred certifications in cloud architecture or AI/ML.

  • Proficiency in Python, SQL, and other relevant programming languages.

  • Familiarity with APIs, and microservices.

  • Experience with implementing disruptive technologies in an organization;

  • Experience with Complex & high volume cloud implementations;

  • Possesses knowledge in financial industry business knowledge as well as knowledge of major data consumption use cases in financial services. 

  • Exhibits knowledge of data architecture concepts and practices. 

  • Demonstrates knowledge of architecture frameworks, methodologies, and tools.