Lead AI Architect - Data Platform

Location: Hybrid in Toronto, Ontario, typically 3 days per week in the Toronto office; the posting also lists the United States as a location.

Salary: CAD $180,000–$210,000 annually, plus performance bonus and benefits.

Company

Banyan Software acquires and grows specialized software businesses worldwide through a buy-grow-and-hold-for-life model, providing shared AI expertise and operational support.

What you will do

• Define and own the target-state data and AI architecture for the organization.
• Design and build a governed AWS data lake using services such as S3, Glue, Lake Formation, Athena, Redshift, and open table formats.
• Establish AI experimentation capabilities, including model access, RAG, evaluation, observability, and cost controls.
• Define data contracts, schemas, domain models, ingestion patterns, lineage, and infrastructure-as-code stahirify.globalrds.
• Partner with business analysts and functional leaders in Finance, M&A, and Business Development to translate use cases into platform requirements.
• Build the platform team, own reliability and costs, and represent the architecture to executives, portfolio companies, and partners.

Requirements

• 10+ years building production data and AI platforms at meaningful scale.
• Deep hands-on AWS experience with S3, IAM, KMS, networking, Glue, Lake Formation, Athena, Redshift, SageMaker, Bedrock, and EKS or ECS.
• Strong data architecture experience with lakehouse patterns, Iceberg, Delta or Hudi, data modeling, ingestion, orchestration, and lineage.
• Experience with AI/ML platform patterns including feature stores, model registries, experiment tracking, prompt and evaluation frameworks, RAG, and agentic workflows.
• Strong Python and SQL skills, plus Terraform or AWS CDK experience; able to write code, ship infrastructure, review pull requests, and debug production issues.
• Experience leading small teams, mentoring engineers, setting hiring stahirify.globalrds, and communicating architecture decisions to technical and executive audiences.

Nice to have

• Experience in private-equity-backed or holding-company environments with multiple business units and inconsistent source systems.
• Experience designing AI guardrails for non-public, regulated, or competitively sensitive data.
• Experience treating internal platforms as products with users, SLAs, and adoption strategies.
• Experience with Snowflake, Databricks, or growth-stage platform teams.

Culture & Benefits

• Greenfield platform development with dedicated budget and broad ownership.
• Accountable autonomy and a long-term approach to platform development.
• Competitive compensation, performance bonus, benefits, and long-term upside.
• Hybrid work with regular presence in the Toronto office.

Hiring process

• Submit a resume and a short note describing a data or AI platform architected and shipped to production.
• Explain the key architectural choices and what would be done differently today.