Principal Platform Architect - AI and Data Platforms

What you'll do

As a Principal Architect – AI & Data Platforms, you will play a pivotal leadership role within the Enterprise AI and Emerging Technology team, responsible for shaping and executing the organization’s strategy across AI, Data Platforms, and Data Governance (DG).

You will define and drive the end-to-end architecture vision, ensuring alignment between business strategy, enterprise architecture standards, and modern platform capabilities. This includes leading the design and implementation of scalable AI and data solutions, establishing governance and standards, and guiding large-scale transformation initiatives.

You will work closely with stakeholders across business and technology teams to build future-ready AI and data ecosystems, while leading architectural practices and mentoring teams.

Strategy & Architecture Leadership

• Define and evolve the AI and Data Platform architecture strategy and roadmap, aligned with enterprise business priorities

• Establish future-state architecture vision across AI, data, analytics, and governance domains

• Develop and maintain architecture models, standards, and roadmaps that guide technology investments and delivery

• Lead enterprise-wide solution blueprints covering data platforms, AI pipelines, BI, and governance capabilities

Platform & Technology Leadership

• Design and evolve modern data platforms (e.g., Lakehouse architectures, data engineering pipelines, BI/reporting ecosystems)

• Architect scalable AI/ML systems leveraging cloud platforms such as Azure (preferred), or GCP

• Lead adoption of event-driven, streaming, and integration architectures across enterprise systems

• Evaluate emerging technologies and guide build vs. buy and innovation decisions

Governance, Standards & Compliance

• Enforce AI, data, and architecture governance standards in collaboration with enterprise governance functions

• Ensure solutions align with architecture principles, security standards, and compliance requirements

• Contribute to the evolution of enterprise architecture frameworks, practices, and processes

• Lead architecture reviews and govern solution design through project lifecycle gates

Collaboration & Stakeholder Engagement

• Partner with business and technology stakeholders to translate requirements into architecture solutions

• Drive cross-functional alignment across data engineers, data scientists, BI teams, and platform teams

• Present architectural strategies and solutions to senior leadership and executive stakeholders

• Advocate for enterprise architecture practices and promote technology standardization and reuse

Leadership & Practice Development

• Lead and mentor architecture team members and contribute to capability growth (including direct reports where applicable)

• Drive continuous improvement in engineering practices, performance optimization, and solution quality

• Foster a culture of innovation, collaboration, and technical excellence across AI and data domains

What you bring

• 5–10+ years of experience in enterprise architecture, data platforms, or AI/ML solutions

• Proven experience delivering large-scale, complex solutions across AI and data ecosystems

• Agentic AI experience (Tool Usage, Agentic Orchestration Frameworks, LLMs, Testing and Evaluation, AgentOps)

• GenAI (LLMs, Monitoring, Testing and Evaluation, LLMOps, Observability, RAG)

• Data platforms & lakehouse architectures (e.g., ADLS Gen2, Databricks, Synapse, ETL/ELT, Unity Catalog)

• MLOps technologies (ML, NLP)

• Cloud platforms (Azure preferred; AWS/GCP knowledge beneficial)

• Big data technologies (e.g., Spark, Hadoop)

• DevOps & CI/CD practices, Infrastructure as Code (Terraform, etc.)

• Containerization and orchestration (Docker, Kubernetes)

Leadership Skills

• Strong strategic thinking and enterprise architecture leadership capabilities

• Excellent communication and storytelling skills, with ability to engage executive audiences

• Ability to operate effectively in complex, evolving environments

• Collaborative mindset with a focus on value delivery, standardization, and scalability

Education

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (PhD considered an asset)

This posting represents an existing vacancy within our organization.

We may use artificial intelligence tools as part of our recruitment process to assist in the initial screening of resumes. All hiring decisions, including candidate evaluation, selection, and disposition, are made by human recruiters.