Senior AI Engineer

Scotiabank; Toronto (OH); On-site; USD 66,274 - 95,729; Full time

Benefits offered by this job

Flexible benefit programs

Job summary

Scotiabank is seeking a Senior AI Engineer in Toronto, Ohio, responsible for designing and operationalizing AI solutions in a regulated banking environment. This role involves leadership across AI engineering and MLOps, ensuring solutions are secure and scalable. Candidates should have extensive experience in cloud engineering and AI systems, particularly in regulated industries. Scotiabank offers benefits tailored to support diverse health needs.

Qualifications

• 8+ years of experience in cloud engineering, with 5+ years focused on AI/ML systems.
• Hands-on experience deploying AI solutions in cloud environments.
• Deep understanding of production concerns: reliability, scalability, observability, cost, and security.

Responsibilities

• Act as a technical lead for AI engineering initiatives.
• Define and contribute to reference architectures for AI development.
• Design and implement production-grade AI services and pipelines.

Skills

Python

SQL

Cloud engineering

AI/ML systems

MLOps / LLMOps tooling

Model risk management

Education

Bachelor’s degree in Computer Science or Engineering

Tools

Azure

Google Cloud Platform (GCP)

Job description

Purpose

The Senior AI Engineer is a senior technical individual contributor responsible for designing, building, and operationalizing enterprise‐grade AI solutions in a highly regulated banking environment. This role provides deep technical leadership across AI engineering, MLOps/LLMOps, and governance by design, ensuring AI solutions are secure, scalable, auditable, and production ready.

What You’ll Do

• Act as a technical lead for AI engineering initiatives, owning design decisions for complex, high‑impact AI solutions.
• Define and contribute to reference architectures, reusable patterns, and “golden paths” for AI development and deployment across the bank.
• Review and approve AI solution designs to ensure alignment with platform standards, security controls, and governance requirements.
• Design and implement production‑grade AI services and pipelines (batch and real‑time) with a focus on reliability, performance, and operational excellence in the cloud.
• Lead the packaging and deployment of models as scalable services (APIs, jobs, agents) with clear SLAs, monitoring, alerting, and runbooks.
• Own complex problem resolution across environments, including production incidents related to AI systems.
• Embed AI governance directly into engineering workflows, covering security and access controls, data classification and handling, model risk management, privacy and consent controls, responsible AI principles, and auditability and regulatory traceability.
• Partner closely with Risk, Compliance, Legal, and Architecture teams to ensure AI solutions meet internal and external regulatory expectations.
• Lead implementation of Generative AI patterns such as Retrieval‑Augmented Generation (RAG), embeddings, semantic search, and agent workflows.
• Ensure GenAI solutions are governed with approved data sources, controlled access, logging, and retention policies.
• Define evaluation and monitoring approaches for GenAI outputs in regulated use cases.
• Design and implement automated ML/LLM delivery pipelines covering training, evaluation, approval, deployment, and rollback, establishing standards for model versioning, reproducibility, environment isolation, and controlled releases.
• Reduce time‑to‑production while increasing safety, repeatability, and governance through automation.
• Mentor senior and mid‑level engineers, raising the overall technical bar across AI engineering.
• Contribute to internal standards, documentation, and knowledge sharing.

What You’ll Bring

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 8+ years of experience in cloud engineering, with 5+ years focused on AI/ML systems.
• Expert‑level proficiency in Python, SQL, and cloud infrastructure.
• Hands‑on experience deploying AI solutions in cloud environments (Azure and GCP).
• Deep understanding of production concerns: reliability, scalability, observability, cost, and security.
• Experience delivering AI solutions in regulated industries (banking, financial services, insurance, healthcare).
• Strong familiarity with model risk management, audit requirements, and regulatory review processes.
• Hands‑on experience with enterprise MLOps / LLMOps tooling and platform design.
• Experience designing platform‑level AI capabilities, not just individual models.

What’s in it for you?

Scotiabank offers flexible benefit programs designed to support your unique family, financial, physical, mental, and social health needs.

Location: Canada – Ontario – Toronto