Additional Information
The Lead Data AI Architect is responsible for translating business strategy into secure, scalable data and AI architectures. This role assesses business requirements, defines and approves technical specifications and architecture decisions, and guides delivery teams in building modern data platforms, analytics solutions, and AI/ML/GenAI products. The Lead Data AI Architect is a senior domain expert who sets standards, patterns, and governance for data and AI across the organization.
Position Responsibilities:
Lead end-to-end architecture for modern data and AI solutions (enterprise data lake, data warehouse, streaming, analytics, ML, and GenAI) that support multiple business functions.
Define and evangelize reference architectures and reusable patterns for data, ML, and GenAI (including MLOps/LLMOps/AIOps), and guide delivery teams on implementation.
Stay current with emerging technologies and practices across data engineering, machine learning, and Generative AI (e.g., RAG, vector search, model fine-tuning, and orchestration).
Evaluate and integrate Azure-native and partner technologies that enhance data processing, storage, analytics, and AI model lifecycle management (CI/CD, testing, monitoring, and cost controls).
Ensure interoperability, data consistency, and responsible AI through strong API/data standards, metadata management, security-by-design, privacy, and model governance.
Conduct discovery to understand current-state data and AI landscapes, including platforms, pipelines, models, and key use cases.
Ensure solution architectures align with business strategy, enterprise technology standards, and data/responsible AI governance requirements.
Document and formalize an approved inventory of data and AI capabilities, tools, and controls, ensuring alignment with strategic objectives.
Expand and govern a catalogue of reusable patterns for data, ML, and GenAI to promote consistency, efficiency, and adherence to best practices.
Create and continuously refine target data and AI reference architectures utilizing Azure services to achieve optimal performance, scalability, security, and cost efficiency.
Identify and recommend opportunities to improve platform reliability, observability, data quality, model performance, and cost optimization.
Partner with engineering, product, data science, security, and risk teams to enable adoption of data/AI patterns, and provide architecture guidance through delivery.
Define and maintain architecture documentation standards, ensuring accessibility, version control, and compliance.
Maintain a centralized repository for data and AI architecture artifacts, including standards, reusable patterns, and governance decisions.
Required Qualifications:
10+ years of experience in data/analytics architecture, with 3+ years designing AI/ML solutions in production (GenAI experience strongly preferred).
Bachelor's degree in Computer Science, Engineering, Information Systems, Data/AI, or a related field. Master's degree preferred.
Proven experience architecting on Azure across data and AI services (e.g., Data Lake/Databricks/Synapse/Fabric as applicable; Azure AI services), ideally within financial services and/or insurance.
Strong understanding of data governance, data modeling, integration, metadata management, and privacy/security controls; able to extend these practices to AI/GenAI governance.
Strong architecture leadership skills: drive decisions, manage trade-offs, and influence across teams while maintaining delivery focus.
Excellent communication and stakeholder management skills, with the ability to translate complex data/AI concepts for technical and non-technical audiences.
Experience with modern engineering practices (IaC, CI/CD), and with MLOps/LLMOps concepts such as model/prompt versioning, evaluation, monitoring, and deployment patterns.
Relevant certifications in Azure (Architecture/Data/AI) are a plus.
Manulife · Toronto, On, Canada