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Description
Requisition ID: 233423
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
We are seeking a passionate and execution-focused AI Engineer to join our high-impact engineering team in Global Wealth Management Technology (GWMT). This role is ideal for an individual contributor who thrives in a fast-paced, agile environment and is ready to design, build, and deploy production-grade AI solutions with minimal supervision. You will be surrounded by innovators solving some of the most pressing challenges in wealth management through intelligence-driven systems. Scotiabank’s Global Wealth Management (GWM) division plays a critical role in delivering personalized financial advice, investment management, and estate planning solutions to clients across Canada and around the world. As part of this trusted and forward-looking organization, you’ll join a high-performing technology team focused on building intelligent, secure, scalable platforms that enhance client and advisor experiences. Working within GWM means applying your AI expertise to real-world financial challenges—helping shape the next generation of wealth services through data-driven innovation and responsible engineering. If you’re motivated by meaningful impact, collaboration, and continuous learning, this is where your work will matter.
Is this role right for you? In this role you will:
Scotiabank is a leading bank in the Americas. Guided by our purpose: “for every future”, we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.
Requisition ID: 233423
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
We are seeking a passionate and execution-focused AI Engineer to join our high-impact engineering team in Global Wealth Management Technology (GWMT). This role is ideal for an individual contributor who thrives in a fast-paced, agile environment and is ready to design, build, and deploy production-grade AI solutions with minimal supervision. You will be surrounded by innovators solving some of the most pressing challenges in wealth management through intelligence-driven systems. Scotiabank’s Global Wealth Management (GWM) division plays a critical role in delivering personalized financial advice, investment management, and estate planning solutions to clients across Canada and around the world. As part of this trusted and forward-looking organization, you’ll join a high-performing technology team focused on building intelligent, secure, scalable platforms that enhance client and advisor experiences. Working within GWM means applying your AI expertise to real-world financial challenges—helping shape the next generation of wealth services through data-driven innovation and responsible engineering. If you’re motivated by meaningful impact, collaboration, and continuous learning, this is where your work will matter.
Is this role right for you? In this role you will:
- Design, implement, and manage Generative AI use cases for production use.
- Engineer robust data pipelines and perform feature extraction using structured and semi-structured data.
- Build, test, and iterate on agentic systems, leveraging LLMs for autonomous task execution.
- Contribute to retrieval-augmented generation (RAG) systems and agent memory structures.
- Automate LLM pipelines including preprocessing, training, evaluation, and retraining workflows.
- Implement CI/CD for AI solutions and deploy models on cloud infrastructure (Azure, GCP).
- Apply foundational LLMOps practices—version control, model reproducibility, performance monitoring.
- Ensure operational reliability through containerization (Docker, Kubernetes) and basic IaC templates.
- Uphold model governance, data compliance, and security in collaboration with DevOps and InfoSec.
- 3–5 years of professional experience in enterprise software development, AI/ML engineering, MLOps, LLMOps, or applied data science.
- Proficient in Python, TypeScript, Spring (preferably Spring AI), React, and major ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Strong grasp of GenAI fundamentals, including multi-agent systems.
- Experience building ML pipelines using tools like MLflow, Kubeflow, or Airflow.
- Working knowledge of containerization (Docker, Kubernetes) and CI/CD workflows.
- Cloud experience with GCP Vertex AI and/or Azure ML.
- Understanding of data wrangling, feature stores, and basic drift detection.
- Familiarity with agent frameworks or multi-agent LLM setups is a plus
- Exposure to RAG workflows and experience using managed vector databases such as Azure AI Search or Vertex AI Matching Engine.
- Familiarity with orchestration frameworks such as LangChain, LlamaIndex, AutoGen, or Semantic Kernel—ideally through experimentation or guided implementations.
- Basic understanding of infrastructure-as-code using tools like Terraform or Azure Resource Manager (ARM).
- Familiarity with observability tools such as Prometheus, Grafana, Dynatrace, Azure Monitor, or GCP Logging.
- Prior exposure to financial services data, models, or regulatory environments is a bonus.
- Familiarity with orchestration and data pipeline tools such as Airflow, dbt, or Google Dataflow is a plus.
- Exposure to explainability concepts (e.g., SHAP, LIME) or metadata tools is a bonus.
- Diversity, Equity, Inclusion & Allyship – We strive to create an inclusive culture where every employee is empowered to reach their fullest potential, respected for who they are, and are embraced through bias-free practices and inclusive values across Scotiabank. We embrace diversity and provide opportunities for all employee to learn, grow & participate through our various Employee Resource Groups (ERGs) that span across diverse gender identities, ethnicity, race, age, ability & veterans.
- Accessibility and Workplace Accommodations – We value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. Scotiabank continues to locate, remove and prevent barriers so that we can build a diverse and inclusive environment while meeting accessibility requirements.
- Upskilling through online courses, cross-functional development opportunities, and tuition assistance.
- Competitive Rewards program including bonus, flexible vacation, personal, sick days and benefits will start on day one.
- Dynamic Ecosystem – Free tea & coffee, universal washrooms, and lots of space for team collaboration.
- Community Engagement – We offer opportunities for community engagement & belonging with our various programs such as hackathons.
Scotiabank is a leading bank in the Americas. Guided by our purpose: “for every future”, we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.
Key Skills
Ranked by relevance
ai
containerization
kubernetes
docker
cicd
gcp
typescript
prometheus
tensorflow
terraform
kubeflow
grafana
pytorch
python
devops
mlflow
react
cloud
mlops
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- Posted
- Jan 09, 2026
- Type
- Full-time
- Level
- Entry
- Location
- Toronto
- Company
- Accelerate Her Future®
Industries
Think Tanks
Categories
Engineering
Information Technology
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3 roles aligned with this opportunity
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