Overview:

We are seeking a seasoned and strategic Senior AI Engineer to join our Global Wealth Management Technology (GWMT) team.

This role is ideal for a hands-on engineer with 5–7 years of experience in building scalable AI/ML systems, enabling production-grade workflows, and mentoring junior engineers. You will drive innovation at the intersection of financial data, cloud infrastructure, and advanced machine learning.

Why Join Us:

• Scotiabank’s Global Wealth Management (GWM) division is dedicated to delivering personalized financial advice, investment management, and estate planning solutions to clients globally.
• As part of this forward-thinking organization, you'll help develop intelligent, secure, and scalable platforms that elevate both client and advisor experiences.
• Your work will directly contribute to the next generation of wealth services through data-driven innovation and responsible AI practices.

Key Responsibilities:

• Lead the development, deployment, and monitoring of complex AI/ML models, including deep learning and natural language applications.
• Build and manage scalable ML pipelines using tools like Airflow, dbt, or Google Dataflow for both batch and streaming data workloads.
• Architect and optimize data workflows using modern data warehousing and lake technologies such as Databricks, BigQuery, Synapse, and Delta Lake.
• Design and operate real-time pipelines using Kafka, Pub/Sub, or similar event-streaming platforms.
• Implement and maintain robust CI/CD processes for ML using MLflow, Kubeflow, or equivalent orchestration tools.
• Develop and deploy models on cloud-native infrastructure using Azure ML, Vertex AI, Docker, and Kubernetes.
• Apply MLOps best practices for versioning, monitoring, retraining, and explainability.
• Mentor L7 engineers, support code reviews, and contribute to a collaborative engineering culture.
• Ensure secure model development, including encryption, RBAC, and compliance with GDPR, PIPEDA, and GLBA.
• Collaborate with data engineers, architects, and product teams to translate financial business problems into machine learning solutions.

Minimum Qualifications:

• 5–7 years of professional experience delivering AI/ML solutions in production environments.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, and XGBoost.
• Experience building or contributing to at least one production-grade RAG pipeline, using vector databases such as Azure Cognitive Search, GCP Vertex AI Matching Engine, FAISS, or Pinecone.
• Hands-on experience with orchestration frameworks like LangChain, LlamaIndex, or Semantic Kernel for chaining context-aware agentic workflows.
• Proven experience with data pipeline orchestration and ML lifecycle tools (e.g., Airflow, MLflow, Kubeflow).
• Hands-on experience with cloud platforms (Azure, GCP) and container orchestration (Docker, Kubernetes).
• Strong understanding of data architecture concepts, including ETL, streaming, and warehouse modeling.
• Demonstrated experience mentoring junior engineers and leading technical initiatives.

Preferred Skills:

• Experience using managed vector search platforms like Azure AI Search and GCP Matching Engine in retrieval-augmented systems.
• Proficiency in Terraform, Pulumi, or Azure Resource Manager (ARM) for infrastructure automation.
• Familiarity with observability and monitoring stacks (Prometheus, Grafana, Azure Monitor, GCP Logging).
• Knowledge of model explainability frameworks such as SHAP, LIME, or counterfactual analysis tools.
• Prior exposure to financial services data, models, or regulatory environments is a bonus.

What’s In It for You

• You'll get to work with and learn from diverse industry leaders, who have hailed from top technology companies around the world.
• We foster an environment of innovation and continuous learning. We have an inclusive and collaborative working environment that encourages creativity, curiosity, and celebrates success!
• We provide employees with an environment that is safe, inclusive, and reflective of all communities by promoting fair and equitable treatment and prioritizing unconscious bias and anti-racism training.
• We offer a competitive total rewards package, including a performance bonus, company matching programs (pension & Employee Share Ownership), generous vacation; health/medical/wellness benefits; employee banking privileges.
• When in person collaboration is required, you can take advantage of our new state of the art ecosystems with a design focus on enabling collaboration through both environment and technology.