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AI Foundation Architect

  • 140 John St, Toronto, ON, M5V 2E4, Canada
  • 1396 Sainte-Catherine O, Montreal, QC, H3G 1P8, Canada

Full-time

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Job details

Job type
Full-time
Experience
Strong experience, 8 years +, designing and owning complex enterprise, solution, cloud, or data architectures in production environments.
Posting language
English
Posted

Original job description

Why Keyrus, Why Now!

Keyrus is an international group of 3,000 experts across 30 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does.

For more than 30 years, we have helped organizations build the data foundations that power intelligent systems. Today, we go further by designing and operationalizing intelligence that delivers measurable business value.

Building AI capabilities is only part of the challenge. Real transformation happens when those capabilities work within existing business systems, data environments, workflows, and processes.

At Keyrus, you'll work closely with clients to design the architecture and technical foundations that turn AI opportunities into secure, scalable, production-ready solutions.

Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.

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.

About Keyrus

At Keyrus, we help organizations move from experimental to industrialized AI, from isolated agents to orchestrated systems, and from insight to execution.

As Architects of Intelligence, we design the Operating System of the intelligent enterprise, embedding intelligence into business processes so that it creates sustainable, measurable value.

Powered by our proprietary Human Orchestrated Model™ (HOM), we architect reliable:

  • Intelligence Foundations
  • Human in Command governance
  • Performance Steering

With over 30 years of expertise and 3,000 experts across 30 countries, we build adaptive, resilient intelligent environments where technology amplifies human capability and performance compounds over time.

AI does not transform businesses. Architected intelligence does.

For more information: www.keyrus.com

More about this job

Responsibilities

The AI Foundation Architect will design secure, scalable technical foundations for enterprise AI and agentic solutions. They will lead architecture discovery, define design standards, and guide multidisciplinary engineering teams to ensure successful production deployments.

Requirements

Candidates must have over 8 years of experience in complex enterprise or cloud architecture with recent practical experience in GenAI and LLM systems. Strong expertise in cloud ecosystems and the ability to evaluate technical trade-offs regarding security, performance, and cost are essential.

Skills

  • Cloud architecture
  • GenAI
  • LLM
  • Agentic systems
  • Enterprise integration
  • Distributed systems
  • Data architecture
  • Security architecture
  • MLOps
  • LLMOps
  • Infrastructure as code
  • API design
  • Microservices
  • Technical leadership
  • Stakeholder management
  • Cloud services

Benefits

  • Group insurance
  • RRSP participation plan
  • DPSP participation plan
  • Monthly wellness allowance
  • 4 weeks of paid vacation
  • Language courses
  • Continuous learning access

Visa sponsorship

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Categories

  • Technology
  • Software
  • Data & Analytics
  • Consulting
  • Engineering

Keywords

  • AI Foundation Architect
  • GenAI
  • LLM
  • Agentic Systems
  • Cloud Architecture
  • AWS
  • Azure
  • GCP
  • Data Architecture
  • Lakehouse
  • Data Mesh
  • MLOps
  • LLMOps
  • CI/CD
  • Kubernetes
  • Terraform
  • Microservices
  • API
  • IAM
  • Enterprise Integration
  • Amazon Bedrock
  • Vertex AI
  • LangGraph
  • AI Governance
  • Distributed Systems
  • Observability
  • Resilience
  • Consulting
  • Architecture Patterns
  • Human Orchestrated Model

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