AI Solutions Architect

Volaris Group; Calgary; On-site; CAD 140,000 - 190,000; Full time

Job summary

Volaris Group seeks an AI Solutions Architect to define technical architecture, standards, and reusable AI patterns enabling our businesses to adopt and operationalize AI at scale. You will lead enterprise AI architecture rather than traditional software development, collaborating with CEOs, product leaders, and engineering teams to deliver scalable, secure AI solutions.

You will guide the AI pods, embed governance, and build reusable assets while each business retains ownership of its

Qualifications

• Experience in enterprise software architecture and solution architecture
• Hands-on AI/ML or intelligent automation delivery experience
• Designing cloud-native, API-first architectures with AI integration
• Experience embedding AI tools into engineering workflows
• Strong leadership and mentoring across multiple teams

Responsibilities

• Define and maintain the Portfolio AI Reference Architecture
• Evaluate enterprise AI platforms and build reference implementations
• Set engineering standards across the AI stack (evaluation, testing, observability)
• Embed AI coding agents and automated testing within the SDLC
• Mentor AI Champions and AI Pods; conduct architecture reviews
• Ensure security, privacy, auditability, governance and Responsible AI compliance

Skills

Enterprise architecture

Solution architecture

Cloud leadership

Mentoring teams

Technical communication

Tools

Azure Cloud

AWS Cloud

Google Cloud

LangChain

OpenAI APIs

Anthropic APIs

Job description

Job Summary

About Us

The Portfolio is a diverse collection of software businesses operating across multiple vertical markets within the Volaris Group, a subsidiary of Constellation Software Inc. (CSI). Each business operates independently while benefiting from a shared operating model focused on long-term value creation, operational excellence, and sustainable growth.

Artificial Intelligence Is a Strategic Priority Across The Portfolio—not Simply To Deploy AI Tools, But To Transform How Our Businesses Operate, Build Products, Engage Customers, And Create Measurable Commercial Value. Our Portfolio AI Transformation Strategy Establishes a Common AI Operating System Built On

Shared assets and decentralized execution

Executive-led AI transformation

Responsible AI governance

Job Description

The Role

As AI Solutions Architect, you will partner to define the technical architecture, standards, and reusable solution patterns that enable our businesses to adopt and operationalize AI. This is a senior technical leadership role focused on enterprise AI architecture rather than traditional software development.

Working alongside Business CEOs, Product Leaders, engineering teams, AI Champions, and AI Pods, you will design scalable AI solutions that accelerate product innovation, automate business processes, and improve customer outcomes while keeping them secure, maintainable, and aligned with enterprise architecture principles. You will support AI Work Pods with architectural guidance, technical coaching, and reusable frameworks, while each business retains ownership of its own implementation.

Key Relationships

• Head of Artificial Intelligence: Reporting to and escalation.
• AI Transformation Lead: Matrix to align technical architecture with transformation delivery.
• Business CEOs, Product Leaders, AI Champions, and AI Pods across participating businesses.
• Product Experts, engineering teams, and Security, Infrastructure, and Engineering functions, on delivery, enterprise standards, and Responsible AI.

Key Responsibilities

• Define and maintain best practices for the Portfolio AI Reference Architecture, its guiding principles, and reusable, secure solution patterns that align with existing software platforms and technology strategies.
• Evaluate and recommend enterprise AI platforms/technologies and build reference implementations using leading AI tools.
• Set enterprise standards and engineering best practices across the AI stack, spanning model evaluation, testing and validation, observability, performance monitoring, and version management.
• Embed AI coding agents, automated code review, and testing automation across the software development lifecycle, in line with the AI-First Engineering playbook.
• Partner with AI Pods to translate business problems into practical, commercially viable solution architectures, and lead Product Experts and engineering teams through solution discovery, delivery, and implementation.
• Embed security, privacy, auditability, governance, and Responsible AI principles into every solution, supporting compliance with regulatory and customer requirements.
• Mentor engineering teams, AI Champions, and AI Pods, and deliver technical workshops and architecture reviews.
• Build reusable assets for the AI Center of Excellence such as prompt libraries, reference architectures, templates, and playbooks to allow the growth of a portfolio-wide community of technical practice.
• Evaluate emerging AI technologies, run proof-of-concept initiatives, and support the Head of AI in shaping the portfolio AI technology roadmap and investment priorities, balancing innovation with architectural discipline. Where technical standards and commercial delivery timelines conflict, elevate to the Head of AI as the final decision-maker.

Success in the First 12 Months

• Portfolio AI Reference Architecture established and adopted.
• Reusable AI components developed and adopted across multiple businesses, reducing duplicated development.
• A reference RAG or agentic pattern documented and piloted in production by at least one AI Pod within 90 days.

Skills & Experience

• Experience in enterprise software architecture, solution architecture, software engineering, or cloud platform leadership.
• Hands‑on experience delivering AI, machine learning, or intelligent automation solutions.
• Experience embedding AI coding agents and automated testing/code‑review tools into engineering workflows.
• A strong background designing enterprise, cloud‑native, and API‑first architectures and integrating AI into SaaS products, plus a track record developing reusable frameworks and defining architecture standards and governance.
• The judgment to balance innovation with operational stability, and the influence to shape architectural decisions across multiple businesses.
• Strong technical leadership, mentoring, and systems‑thinking skills, with the ability to communicate complex concepts to non‑technical stakeholders.
• Pragmatic, collaborative, and detail‑oriented, with the strong engineering mindset and a bias toward practical delivery.
• Curious about emerging AI and continuously learning, calm under pressure, and committed to responsible AI.

Technical Expertise

Must-have

• Generative AI
• Large Language Models (LLMs)
• Agentic AI
• Retrieval‑Augmented Generation (RAG)
• AI orchestration frameworks
• Prompt engineering
• Model evaluation
• AI observability
• AI security
• Vector databases

Nice‑to‑have

• Enterprise integration patterns
• Cloud platforms (Azure, AWS, and Google Cloud)
• Microsoft Copilot ecosystem
• OpenAI and Anthropic APIs

Experience with technologies such as Semantic Kernel, LangChain, AutoGen, Model Context Protocol (MCP), or similar AI orchestration frameworks will be highly regarded.

Worker Type

Regular

Number Of Openings Available

1