AI Automation Engineer (Data Products)

Software International; Montreal; Hybrid; CAD 80,000 - 100,000; Part time

Job summary

A prominent software company is seeking an AI Automation Engineer (Data Products) to lead the automation of data product creation. The ideal candidate will have over 10 years of experience in data architecture, hands-on skills with Microsoft Fabric and SAP integration, and strong programming abilities in Python and SQL. The role involves designing automation solutions, integrating existing frameworks, and collaborating with stakeholders. This hybrid position is based in Montreal with some travel to Mississauga.

Qualifications

• 10+ years of experience in data/AI architecture, workflow automation, or platform engineering roles.
• Hands-on experience with Microsoft Fabric or similar modern tools, SAP BW integration, and MCP workflow integration.
• Strong programming skills in Python and SQL.

Responsibilities

• Analyze current data product creation workflows and implement AI/automation solutions.
• Operationalize existing automation tools and integrate with governance processes.
• Create patterns and templates for efficient data product creation.

Skills

Data/AI architecture

Workflow automation

Platform engineering

Python

SQL

DataOps concepts

Collaboration

Communication

Tools

Microsoft Fabric

SAP BW

MCP server

Job description

About the job AI Automation Engineer (Data Products)

Software International (SI) supplies technical talent to a variety of clients ranging from Fortune 100/500/1000 companies to small and mid-sized organizations in Canada/US and Europe.

We currently have an long term contract role as a AI Automation Engineer (Data Products) with our global SAP consulting client, working at a large CPG clients' locations either in Montreal or Mississauga. This is a hybrid role with some weekly in office visits (2 days onsite).

Type: Contract

Duration: 6 months to start + 6 month extensions

Rate: C2C - open based on overall experience (target range is about $60-90/hr)

Language Requirements: English (French is a nice to have)

Location: Hybrid - Montreal or Mississauga

Role Summary

Our client is seeking an AI/Automation Engineer to lead the automation of data product creation. This role focuses on applying and integrating existing AI and automation frameworks (such as MCP) to streamline how data products are designed, built, and managed. The ideal candidate blends architectural vision with hands-on development skills, ensuring scalable, production-ready automation that accelerates Krugers Data Product Foundation.

Key Responsibilities:

• Automation Design & Implementation: Analyze current data product creation workflows, design and implement AI/automation solutions using AI models and the MCP framework.
• Integration & Enablement: Operationalize existing AI/automation tools and frameworks into data pipelines, ensuring seamless integration with governance and lifecycle management processes.
• Standardization & Reuse: Create patterns, templates, and automation assets that make data product creation faster, repeatable, and AI-ready.
• Collaboration: Work closely with data engineers, architects, and business stakeholders to deliver high-quality, standardized data products.
• Operational Excellence: Implement observability, monitoring, and quality controls for automation pipelines.
• Data Contracts & Catalog: Support the definition and automation of data contracts, improving discoverability through the Data Product Catalog.
• Continuous Innovation: Stay up to date on emerging automation frameworks, AI-assisted development tools, and best practices to further enhance data product creation.

Qualifications:

• 10+ years of experience in data/AI architecture, workflow automation, or platform engineering roles.
• Hands-on experience with Microsoft Fabric (or similar modern tools), SAP BW integration, and MCP server implementation and MCP workflow integration.
• Strong programming skills (Python, SQL) and proficiency in workflow/automation frameworks.
• Knowledge of data governance, DataOps concepts (monitoring, observability, lifecycle management).
• Demonstrated ability to design automation patterns and deploy them at scale in enterprise environments.
• Strong collaboration and communication skills across technical and business teams. Able to convert stakeholders' business requirements into AI implementation solutions.