AI Solutions Architect

This is a fully remote position, open to applicants in Canada.

📋 Description

• Define and uphold the Portfolio AI Reference Architecture, along with its guiding principles and reusable secure solution frameworks.

• Assess and suggest enterprise AI platforms and technologies.

• Create reference implementations utilizing leading AI tools.

• Set engineering standards for model evaluation, testing, validation, observability, performance monitoring, and version management.

• Integrate AI coding agents, automated code review, and testing automation into the software development lifecycle.

• Convert business challenges into feasible, commercially viable AI solution architectures.

• Guide Product Experts and engineering teams throughout the solution discovery, delivery, and implementation processes.

• Incorporate security, privacy, auditability, governance, and Responsible AI principles into solutions.

• Mentor engineering teams, AI Champions, and AI Pods.

• Conduct technical workshops and architecture reviews.

• Develop reusable assets for the AI Center of Excellence, including prompt libraries, reference architectures, templates, and playbooks.

• Assess emerging AI technologies and initiate proof-of-concept projects.

• Assist the Head of AI in defining the AI technology roadmap and investment priorities.

• Raise issues between technical standards and commercial timelines to the Head of AI.

⛳️ Requirements

• Proven experience in enterprise software architecture, solution architecture, software engineering, or cloud platform leadership.

• Practical experience in delivering AI, machine learning, or intelligent automation solutions.

• Experience in integrating AI coding agents and automated testing/code-review tools within engineering workflows.

• Strong expertise in designing enterprise, cloud-native, and API-first architectures.

• Familiarity with incorporating AI into SaaS products.

• Documented success in developing reusable frameworks and establishing architecture standards and governance.

• Ability to balance innovation with operational stability.

• Capability to influence architectural decisions across multiple business units.

• Exceptional technical leadership, mentoring, systems-thinking, and communication skills.

• Proficiency in explaining complex concepts to non-technical stakeholders.

• A pragmatic, collaborative, and detail-oriented engineering mindset.

• Strong commitment to responsible AI practices.

• Essential expertise in Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), AI orchestration frameworks, prompt engineering, model evaluation, AI observability, AI security, and vector databases.

• Desirable expertise in enterprise integration patterns, Azure, AWS, Google Cloud, Microsoft Copilot ecosystem, OpenAI APIs, and Anthropic APIs.

• Experience with Semantic Kernel, LangChain, AutoGen, Model Context Protocol (MCP), or similar AI orchestration frameworks is highly valued.

🏝️ Benefits

• Competitive compensation.

• Comprehensive benefits package.

• Opportunity to learn from industry leaders.

• Thriving entrepreneurial environment.

• Commitment to equal opportunity employment.