Publié il y a 5 jours
Chief AI Architect
@ ITSector
Montréal, Québec
SIGNAUX
En bref
ITSector is hiring a Chief AI Architect for a full-time role that sets the enterprise architectural vision for generative and agentic AI. The work covers AI principles, reference architectures, governance guardrails and advising executives on AI investments and vendor choices. The posting asks for at least 15 years of enterprise or solution architecture experience and fluency in English and French.
Responsabilités :
- Establish AI principles, guardrails and reusable patterns
- Lead architectural vision for generative and agentic AI
- Define enterprise patterns for agentic systems
- Advise executives on AI investments and vendor choices
- Oversee AI risk management and architectural escalation
Résumé des exigences :
- Degree in computer or electrical engineering or similar
- Minimum 15 years of enterprise or solution architecture experience
- Deep expertise in machine learning, generative AI and agentic systems
- Knowledge of AI governance, ethics and regulatory constraints
- Solid knowledge of data platforms, MLOps and AWS or Azure
- English and French communication skills
Outils et compétences
Source et dates
Type de source non vérifié · apify-linkedin
- Date publiée par l’employeur
- 2026-11-08
- Première détection par notre source
- 2026-11-14
- Mise à jour du dossier source
- 2026-11-14
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Chef d’équipe |
| Expérience | 15 an(s) et plus |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English, French |
| Formation | Baccalauréat (exigé) |
| Domaines d’études | Computer Engineering, Electrical Engineering |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
ITSector
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 1 |
Description
Let's take a look at the profile we are looking for:
- Ambitious people with a passion for this area;
- Degree in Computer Engineering, Electrical Engineering or similar;
- Minimum 15 years of experience in enterprise and/or solution architecture, including significant hands-on experience in AI-related domains;
- Deep expertise in AI technologies, including machine learning, generative AI, agent-based systems, and the enterprise platforms required to operationalize them;
- Strong understanding of AI governance, ethics, regulatory constraints, and risk management in large organizations;
- Demonstrated experience designing AI reference architectures, defining enterprise guiding principles, and shaping scalable architectural patterns;
- Solid knowledge of data platforms, MLOps / LLMOps, and cloud-native AI services such as AWS and Azure;
- Strong leadership presence with the ability to influence executives and senior peers, challenge stakeholders constructively;
- Written and verbal communication skills (English and French);
- Ability to work effectively and manage deadlines;
- Sense of responsibility, commitment and integrity;
- Focus on innovation, dynamism, autonomy and teamwork.
- Establish pragmatic AI principles, guardrails, and reusable patterns that accelerate delivery while ensuring consistency, reuse, and control across the organization;
- Lead the architectural vision for generative and agentic AI, ensuring solutions are secure-by-design, auditable, and operable at enterprise scale;
- Define enterprise patterns for agentic systems, including autonomy boundaries, human-in-the-loop controls, lifecycle management, and safe-stop mechanisms;
- Partner with AI delivery, governance, business, data, and technology stakeholders to drive a coherent enterprise AI approach, clarify decision rights, and translate opportunities into scalable golden paths;
- Advise executives on AI-related investments, platform and vendor choices, adoption sequencing, and trade-offs between speed, control, and risk;
- Oversee AI risk management, emerging technology assessment, and architectural escalation for complex or high-risk AI initiatives.
Journal
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