software design engineer

Scotiabank; Toronto; On-site; CAD 125,000 - 150,000; Full time

Job summary

A leading financial institution in Toronto is seeking an experienced Senior AI Engineer. In this role, you will design and deploy AI/ML systems that meet business and regulatory needs. Ideal candidates will have 7-9 years of experience in AI/ML, particularly in financial services, and possess strong technical skills in cloud technologies and data management. The position offers a full-time permanent role with competitive hourly compensation ranging from $33.46 to $84.62.

Qualifications

• 7-9 years of experience in AI/ML systems.
• Strong applied experience with retrieval-augmented generation systems.
• Proficiency in orchestration frameworks such as LangChain or LlamaIndex.

Responsibilities

• Architect scalable and secure ML solutions.
• Lead design of complex AI/ML systems.
• Collaborate with engineering leads on end-to-end ML infrastructure.

Skills

AI/ML systems architecture

Financial services data experience

ML Ops pipelines

Cloud-native technologies

Containerization (Docker, Kubernetes)

Tools

Azure

GCP

Terraform

Airflow

Prometheus

Job description

Senior AI Engineer

Posted on October 14, 2025 by Scotiabank

Job details

Requisition ID: 226991

Join a purpose-driven winning team, committed to results, in an inclusive and high-performing culture.

Overview

Global Wealth Management Technology (GWMT) is seeking an exceptional and forward-thinking Senior AI Engineer to help shape and execute the next generation of intelligent solutions within GWMT. This role is ideal for a highly competent engineer with 7‑9 years of hands‑on experience who can architect robust AI/ML systems, align with enterprise strategy, and elevate technical excellence across domains. You will play a pivotal role in translating business vision into AI‑driven outcomes, championing scalable design, and fostering a collaborative engineering culture.

Why Join Us

• Scotiabank's Global Wealth Management (GWM) division empowers millions of clients worldwide with personalized financial planning, investment strategies, and advisory services.
• As part of GWMT, you'll work on high‑impact problems that blend financial insight with advanced machine learning.
• Shape cloud‑native, secure, and explainable AI/ML systems that enhance advisor intelligence and client experience while aligning to regulatory, operational, and strategic priorities.
• Our engineering culture values autonomy, intellectual rigor, and business alignment.
• We are building intelligent platforms that integrate with every layer of our advisory experience.
• Collaborate with industry veterans and technologists passionate about impact, precision, and doing meaningful work at scale.

Key Responsibilities

• Architect scalable and secure ML solutions using cloud‑native technologies (Azure, GCP) and distributed processing frameworks.
• Lead the design, integration, and optimization of complex AI/ML systems including RAG, agentic workflows, and multi‑model orchestration.
• Develop and maintain advanced ML Ops pipelines with robust CI/CD, testing, retraining, and observability baked in.
• Translate evolving business objectives and regulatory requirements into practical AI frameworks and platform capabilities.
• Own technical vision and best practices around explainability, privacy, compliance (e.g., PIPEDA, GLBA, GDPR), and governance.
• Collaborate closely with engineering leads, enterprise architects, and data teams to establish end‑to‑end ML infrastructure that is resilient, performant, and measurable.
• Mentor senior and junior engineers alike, guiding architectural reviews, solution scoping, and delivery excellence.

Minimum Qualifications

• 7‑9 years of experience building and deploying AI/ML systems in production, with a track record of leading end‑to‑end architecture.
• Demonstrated experience with financial services data, models, and regulatory environments (e.g., compliance logging, auditability, explainability).
• Strong applied experience with retrieval‑augmented generation (RAG) systems and vector databases, including Azure Cognitive Search, GCP Matching Engine, FAISS, or Weaviate.
• Proficiency in orchestration frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
• Hands‑on expertise in infrastructure‑as‑code tools such as Terraform, ARM, or Pulumi.
• Deep understanding of ML lifecycle tools, including Airflow, MLflow, Kubeflow, and model registry/versioning.
• Expertise in observability stacks such as Prometheus, Grafana, Azure Monitor, or GCP Cloud Logging.
• Cloud‑native deployment skills (Azure ML, Vertex AI) and containerization (Docker, Kubernetes).

Preferred Skills

• Experience designing federated learning systems or privacy‑preserving ML architectures.
• Familiarity with AI risk and controls frameworks (e.g., model validation, fairness auditing, adversarial robustness).
• Ability to present and defend architectural decisions to both technical and executive audiences.
• Contributor to open‑source ML/AI tools or research publications.

Location and Compensation

• Location: Toronto, ON
• Work location: On site
• Salary: $33.46 to $84.62 per hour
• Terms of employment: Permanent employment, Full time
• Start date: As soon as possible
• Vacancies: 1 vacancy
• Source: CareerBeacon #2163338

Advertised until

2025-11-13