Role details
• Location: Hybrid - Montreal or Toronto, Canada (2 days per week in the office)
• Contract: Permanent, full-time
What you'll architect
As an AI Foundation Architect, you'll design the technical foundations that enable organizations to develop, deploy, and scale AI and agentic solutions in enterprise environments.
You'll connect cloud infrastructure, data platforms, enterprise applications, models, agents, and security capabilities to create reliable architectures that support business needs.
Your focus goes beyond solution design. You'll define architecture principles, make key technical decisions, and guide engineering teams in building secure, scalable, and cost-effective AI systems.
Your responsibilities
• Lead architecture discovery with clients to understand business objectives, existing systems, technical constraints, and AI requirements.
• Define target architectures for production AI and GenAI solutions, integrating models, agents, cloud services, enterprise data, applications, and APIs.
• Own key architecture decisions within the assigned scope, establishing reference patterns, technical boundaries, and design standards.
• Design secure and reliable foundations addressing identity, access, scalability, resilience, observability, and operational requirements.
• Evaluate architecture trade-offs, including model selection, performance, latency, infrastructure costs, and AI consumption patterns.
• Guide AI Engineers, Data Engineers, Software Engineers, and cloud specialists to ensure consistency across technical implementations.
• Advise client stakeholders, review technical designs, and document reusable architecture patterns and decisions.
• Convert successful architecture decisions into reusable Keyrus assets, including reference architectures, decision records, standards, patterns, and design guidance that can strengthen future engagements.
Who you are
You are an experienced technical architect who combines strategic architecture judgment with recent practical understanding of production AI systems. You understand how cloud, data, applications, and AI technologies work together, and you can translate business requirements into practical architecture decisions. You are comfortable evaluating technical trade-offs, guiding engineering teams, and advising clients while respecting specialist ownership. You combine strong technical judgment with clear communication, problem-solving, and leadership skills.
What you bring
Experience
• Strong experience, 8 years +, designing and owning complex enterprise, solution, cloud, or data architectures in production environments.
• Recent experience architecting production GenAI, LLM, or agentic systems, including integration with enterprise applications and operational infrastructure.
• Experience defining reference architectures, technical standards, integration patterns, and architecture decisions.
• Experience designing distributed systems and enterprise integrations across multiple technical environments.
• Ability to evaluate architecture trade-offs involving security, reliability, scalability, performance, maintainability, and cost.
• Experience guiding multidisciplinary engineering teams and advising client architects, technical leaders, and business stakeholders.
Technical skills
• Deep architecture expertise in at least one major cloud ecosystem, such as AWS, Azure, or GCP, including relevant AI services.
• Experience designing architecture for model access and deployment patterns across managed AI services, APIs, open-source models, or comparable enterprise AI environments.
• Strong understanding of GenAI architectures, including LLMs, RAG, AI agents, model integration, and enterprise AI workflows.
• Experience with distributed systems, APIs, microservices, and enterprise integration patterns.
• Knowledge of enterprise data architectures, including lakehouse, streaming, data mesh, or feature stores.
• Understanding of security architecture, IAM, networking, resilience, observability, and production operations.
• Familiarity with MLOps, LLMOps, CI/CD, containers, infrastructure as code, and AI cost optimization.
Nice to have
• Experience with Amazon Bedrock, Azure AI, Vertex AI, or comparable cloud AI services.
• Experience designing multi-agent systems, model routing, or AI orchestration architectures.
• Familiarity with LangGraph, MCP, AI gateways, or similar technologies.
• Experience with Terraform, Kubernetes, or enterprise infrastructure automation.
• Experience with regulated environments, AI governance, or formal architecture review processes.
• Consulting or professional services experience across multiple clients.
What makes you successful
• You turn complex requirements into clear architecture solutions.
• You design secure, scalable, and cost-effective AI foundations.
• You guide technical teams and communicate effectively with clients.
• You make practical architecture decisions that support business value.
What we offer at Keyrus
• A stimulating environment where you can challenge yourself and discover new horizons.
• A strong culture of innovation and entrepreneurship.
• Opportunities to celebrate success through team activities, social events, and special celebrations.
• Comprehensive group insurance for you and your family.
• RRSP and DPSP participation plans.
• Monthly wellness allowance.
• Telecommunication reimbursement.
• 4 weeks of paid vacation.
• Language courses (French and English).
• Access to continuous learning through certifications, conferences, training programs, and industry events.
The expected base compensation for this position ranges from $115,000 to $140,000 CAD, depending on experience, skills, location, and internal equity. This salary range is provided as a guideline and may be adjusted for the selected candidate.
