AI Data and Integration Engineer

We are hiring an AI Data and Integration Engineer, Application Development!

Reporting To: Assistant Vice President IT, Application Development

Full-Time/Part- Time: Full-time

Salary Range: $80,021-$128,034

Posting Date: August 21, 2026

Closing Date: September 21, 2026

Hours of Work: 8:30 a.m. – 5:00 p.m.

Grade: 14.4

Office Location: Toronto Great location! Steps away from the main public transit station

What we offer:
Highly competitive compensation package which includes, base salary, bonus, benefits, and career advancement opportunities!

• Eligibility for benefits is dependent on the terms of employment

The Opportunity:
The AI Data and Integration Engineer reports to the AI Engineering Lead and is the single accountable owner for making trusted, governed data and reliable system connectivity available to First National’s AI enabled mortgage workflows, from design through production.

This is a hands on engineering role within the AI Platform Squad, focused on data contracts, source to target integration with Merlin and enterprise systems, APIs, event integration, document and metadata flows, controlled write back, data quality, lineage, and operational support. This role holds end to end accountability for data and integration delivery, including the batch, service oriented, and legacy interface dependencies that AI enabled underwriting workflows rely on.

How you will contribute:

• Design, build, test, and operate the data and integration components for AI enabled mortgage workflows, including source ingestion, transformation, enrichment, document metadata, reference data, APIs, event flows, exception handling, and controlled write back to core systems.
• Hold end to end integration accountability for AI use cases across Merlin, SQL Server sources, document repositories, enterprise services, and event backbones, so that integration delivery does not fragment across AI, product, data, and architecture teams.
• Translate workflow, policy, reporting, and operational requirements into source to target mappings, canonical data models, interface contracts, validation rules, reconciliation controls, and traceable data lineage, in partnership with the Merlin Product Owner, the Residential Underwriting Business SME, AI Engineers, and application teams.
• Build governed batch and near real time pipelines using approved First National patterns across Databricks and Azure, including Lakeflow or comparable orchestration, Delta Lake bronze, silver, and gold layers, Unity Catalog, SQL Server, document repositories, and enterprise integration services.
• Develop and maintain secure APIs, services, and event integrations using Python, SQL, FastAPI, .NET or comparable technologies, Azure Service Bus, API Management, Git based workflows, automated tests, CI/CD, and infrastructure as code practices.
• Implement data quality and integration controls, including schema validation, completeness, accuracy, timeliness, duplication, referential integrity, reconciliation, error routing, replay, idempotency, observability, alerting, and audit evidence.
• Apply privacy, security, retention, access control, and data governance requirements to structured and unstructured information, including PII handling, Entra ID, RBAC, Key Vault, private connectivity, logging, and least privilege access.
• Support AI Engineers and full stack engineers with reliable, documented interfaces and representative data, diagnose data and integration failures through development, evaluation, UAT, parallel runs, production releases, incidents, and ongoing monitoring, and refactor partner delivered or prototype pipelines into modular, testable, documented, supportable services, contributing reusable connectors, data contracts, mappings, and engineering patterns back to the AI Factory catalog.

The experience you need:

• Bachelor’s degree in computer science, software engineering, data engineering, information systems or a related discipline.
• 5 plus years of progressive data engineering, integration engineering, software engineering, cloud engineering, or related technology experience.
• Strong hands on experience with Python, SQL, APIs, ETL or ELT pipelines, data modeling, automated testing, Git based delivery, CI/CD, cloud services, and production support.
• Practical experience with Microsoft Azure, Databricks or comparable data platforms, Delta Lake, Unity Cat…