- The expected base salary range for this position is $100/Hr - $110/Hr, depending on experience, skills, and internal equity.
- The Company offers a total rewards package in accordance with all applicable federal, provincial, and local laws and requirements.
- Benefit eligibility and offerings vary based on role, employment status, and work location.
- For contractor positions, benefits are limited to those entitlements and protections required by applicable law, which may include (as applicable) vacation pay, public holidays, leaves of absence, and other legally mandated benefits or payments.
- We may use AI-enabled and/or automated tools to support parts of our recruitment process, including application screening, interview scheduling, and candidate communications.
- These tools are used to enhance consistency and efficiency.
- All hiring decisions involve human review and are not based solely on automated processing.

:

- Bank is seeking a highly experienced Full Stack AI Architect - AI Solutions to lead the design, evaluation, and implementation of enterprise-scale Artificial Intelligence solutions across Azure and other cloud.
- This role will focus on architecting next-generation AI capabilities, including Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), Copilot, Gemini, and enterprise AI platforms.
- The ideal candidate will combine deep technical expertise with robust architectural leadership, helping guide AI initiatives from proof-of-concept through production deployment while ensuring scalability, security, governance, and business alignment.

Key Responsibilities:

- Lead the architecture, design, and implementation of enterprise AI and GenAI solutions across complex cloud environments.
- Partner closely with engineering teams to evaluate feasibility, define architecture, and guide implementation from concept to production.

Design and deliver solutions leveraging:





- Gemini and Vertex AI
- Azure OpenAI and Azure AI Foundry
- Copilot Studio
- AI Agents and Agentic AI frameworks
- Retrieval-Augmented Generation (RAG)
- LLM Gateways and Model Routing
- Enterprise APIs and Data Integrations
- Evaluate Azure and other Cloud AI capabilities and recommend the most effective platform based on business and technical requirements.
- Develop architecture blueprints, target-state designs, technical standards, and implementation roadmaps.
- Assess emerging AI technologies and determine their suitability for enterprise adoption.
- Collaborate with Cloud, Security, Data, Risk, Governance, and Architecture teams to ensure solutions meet enterprise standards.
- Define best practices for AI security, governance, observability, resiliency, and operational excellence.
- Present architectural recommendations and technology strategies to engineering teams, senior leadership, and executive stakeholders.
- Drive adoption of responsible AI principles and governance frameworks within the organization.

Required Qualifications:

- 15+ years of experience in software engineering, cloud architecture, solution architecture, or related technology leadership roles.
- Proven experience architecting and delivering enterprise-grade Generative AI and Large Language Model (LLM) solutions.

Hands-on experience with:

- Agentic AI and AI Agents
- Retrieval-Augmented Generation (RAG)
- LLM Gateways and AI Platform Architecture
- Model Routing and Model Consumption Frameworks




- Enterprise API and Data Integration Architectures
- Strong experience implementing AI solutions using Gemini and Vertex AI within enterprise environments.

Extensive Azure AI and cloud architecture experience, including:

- Azure OpenAI
- Azure AI Foundry
- Azure Databricks
- MS Fabric
- Copilot Studio

Strong understanding of enterprise AI operational requirements, including:

- Security and Governance
- Identity & Access Management (IAM)
- Data Privacy and Protection
- Observability and Monitoring
- Reliability and Resiliency
- Cost Optimization and Token Governance
- Ability to influence technical decisions and establish credibility with senior engineering teams.
- Excellent communication, presentation, and stakeholder management skills.

Preferred Qualifications:

- Banking, Financial Services, or Capital Markets experience.
- Experience with Databricks Unity Catalog and Genie.
- Kubernetes and container platform architecture expertise.
- Experience with MLOps, AIOps, and AI platform operations.
- Knowledge of Responsible AI frameworks and AI governance practices.
- Experience working within highly regulated enterprise environments.
- Relevant certifications in Azure, Cloud, AI, Security, or Enterprise Architecture.

Technical Environment:

- Azure OpenAI
- Azure AI Foundry
- MS Fabric
- Azure Databricks
- Copilot Studio
- Gemini
- Vertex AI
- RAG Architectures
- Agentic AI Frameworks
- LLM Gateways
- Kubernetes
- Enterprise APIs
- Cloud Security & IAM
- Observability Platforms

Ideal Candidate Profile:

- The successful candidate is a strategic AI architect who can bridge business objectives with technical execution.
- They possess deep expertise across cloud platforms, GenAI technologies, enterprise architecture, and AI governance while effectively communicating complex concepts to both technical and executive audiences.

📌 Full Stack AI Architect (Toronto)
🏢 Collabera
📍 Toronto