- Evaluate AI frameworks, platforms, and tools to recommend build-versus-buy decisions
- Guide foundation model selection aligned with CBC use cases and infrastructure capabilities
- Lead architecture of AI applications using LLMs, machine learning, deep learning, and NLP
- Develop architectural roadmaps for GenAI, LLM, and agentic business-process initiatives
- Lead integration of scalable AI systems, ML pipelines, and agentic AI workloads
- Monitor emerging AI technologies and assess business value
- Establish standards for model performance, traceability, data lineage, and privacy compliance
- Identify AI use cases from business requirements
- Integrate AI solutions with enterprise applications
- Craft prompts, evaluate outputs, and design automated end-to-end agentic workflows
- Test and refine models for reliability, scalability, and production performance
- Support post-deployment monitoring and governance
- Lead technical discussions with stakeholders and development teams
- Define outcomes, success metrics, and value drivers with business leaders
- Collaborate with ethics and compliance teams on regulatory and governance adherence
- Mentor technical teams on AI architecture best practices

Requirements

- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field
- 3–5 years of experience in software architecture, cloud architecture, data engineering, or AI solutions
- 1–2 years of experience designing enterprise AI or machine learning solutions
- Experience delivering cloud-native AI solutions
- Vendor-specific certifications such as Microsoft Certified: Agentic AI Business Solutions Architect or equivalent AWS/GCP architecture credentials highly valued
- Deep understanding of ML, NLP, and AI application deployment using Python or R
- Knowledge of AI governance frameworks and responsible AI practices
- Experience with data management systems and MLOps tools such as Kubernetes, Git, and model registries




- Exceptional stakeholder management and technical leadership
- Experience in media, broadcasting, or content distribution technology desired
- Familiarity with TOGAF, Zachman, or other enterprise architecture frameworks desired
- Executive communication and product management experience desired
- Compliance expertise in regulated industries desired
- Ability to multitask and manage concurrent or conflicting priorities
- Solid communication and coaching skills
- Ability to work with remote teams
- Candidates may be subject to skills and knowledge testing
- Mandatory criminal record check for candidates advancing in the process

Core Competencies

Demonstrates expertise in AI architecture, including the integration of scalable AI systems and machine learning pipelines, while ensuring compliance with governance frameworks. Proficient in evaluating AI frameworks and leading technical discussions to align AI solutions with business objectives.

Highest-signal resume keywords

- AI Architecture Leadership
- Machine Learning Solutions Design
- Cloud-Native AI Solutions Delivery
- Python or R for AI Deployment
- Vendor-Specific AI Certifications

ATS Optimization Keywords

Hard Skills

- AI Framework Evaluation
- Machine Learning
- Deep Learning
- Natural Language Processing
- Data Management Systems
- MLOps Tools
- Model Performance Standards
- AI Use Case Identification
- Automated Workflow Design
- Model Testing and Refinement

Soft Skills

- Stakeholder Management
- Technical Leadership
- Executive Communication
- Coaching Skills
- Multitasking Ability

Certifications & Qualifications

- Microsoft Certified: Agentic AI Business Solutions Architect
- AWS Architecture Credentials
- GCP Architecture Credentials

Industry Keywords

- Media Technology
- Broadcasting
- Content Distribution
- Enterprise Architecture Frameworks
- Regulated Industries Compliance

Tools & Technologies

- Kubernetes
- Git
- Model Registries
- Cloud Platforms
- AI Governance Frameworks

📌 AI Lead Architect, Software and Platforms Architecture (Montreal)
🏢 Jobtailor
📍 Montreal