JOB TITLE: SENIOR AI ARCHITECT – GENERATIVE AI & ENTERPRISE SOLUTIONS

Location: Toronto, ON (Hybrid)
We are seeking a visionary and technically accomplished Senior AI Architect with deep expertise in Generative AI, LLMs, NLP, and enterprise AI frameworks, preferably with experience in financial services or regulatory sectors. The ideal candidate will lead the design and deployment of scalable AI infrastructures, bridging business objectives with cutting-edge AI strategy and compliance requirements.

REQUIRED QUALIFICATIONS:

• 10+ years of experience in AI/ML architecture with a focus on Generative AI and NLP.
• Proven track record leading AI initiatives in financial services, banking, or regulatory environments.
• Proficiency in LLMs (e.g., GPT, BERT), RAG pipelines, vector and graph databases, and prompt engineering.
• Strong experience with cloud-native development (AWS SageMaker, Azure OpenAI, GCP) and Kubernetes/Docker for containerized deployments.
• Knowledge of AI compliance, security standards, and risk governance frameworks.
• Advanced programming skills in Python, with experience in building production-ready systems.
• Exceptional leadership, communication, and stakeholder management skills.

• Architect and deploy enterprise-grade AI solutions using Generative AI, LLMs, RAG, and deep learning technologies to enhance automation, risk assessment, and financial operations.
• Lead the design of modular AI frameworks that enable secure, compliant, and scalable integration of AI across financial systems.
• Translate complex regulatory and business needs into scalable AI applications through hands-on development and strategic planning.
• Champion AI governance best practices, ensuring alignment with international standards and risk frameworks (e.g., AML, compliance, fraud detection).
• Build and oversee AI-enhanced decision support systems, virtual assistants, and document intelligence tools.
• Collaborate cross-functionally with stakeholders, data scientists, and DevOps teams to deliver production-ready AI solutions.
• Leverage cloud platforms (AWS, Azure, GCP) and Kubernetes for robust model deployment and orchestration.
• Mentor teams, contribute to enterprise roadmaps, and foster innovation within a regulated ecosystem.