Is this role right for you? In this role, you will: Production AI Engineering (Build, Deploy, Run) Implement productiongrade AI services and pipelines (batch and realtime) with strong focus on reliability, performance, and operational excellence in the cloud Execute, manage and support the packaging and deployment of models and solutions 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.

Governanceby

Design (Banking & Regulatory Alignment) Embed AI governance directly into engineering workflows , including: Security and access controls Data classification and handling Model risk management requirements Privacy and consent controls Responsible AI principles Auditability and regulatory traceability Partner closely with Risk, Compliance, Legal, and Architecture teams to ensure AI solutions meet internal and external regulatory expectations.

Generative AI & Advanced AI Capabilities Implementation of Generative AI patterns such as Retrieval

Augmented Generation (RAG), embeddings, semantic search, and agent workflows.

Ensure GenAI solutions are grounded in approved data sources, governed access, logging, and retention policies.

Define evaluation and monitoring approaches for GenAI outputs in regulated use cases.

Enterprise MLOps / LLMOps Implement automated ML/LLM delivery pipelines covering training, evaluation, approval, deployment, and rollback.

Implement standards for model versioning, reproducibility, environment isolation, and controlled releases.

Reduce timetoproduction while increasing safety, repeatability, and governance through automation.

Do you have the skills that will enable you to succeed in this role? We''d love to work with you if you have: Bachelors degree in Computer Science, Engineering, or equivalent practical experience. 3+ years of experience in cloud engineering,



with 3+ years focused on AI/ML systems Expertlevel proficiency in Python, SQL and cloud infrastructure Handson 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.

Handson experience with enterprise MLOps / LLMOps tooling and platform design.

Experience designing platformlevel AI capabilities, not just individual models.

What''s in it for you? 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, adaptable 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 - No matter where you choose to work from; we offer opportunities for community engagement & belonging with our various programs. #AIData

Platforms

📌 Developer, AI Engineering (Toronto)
🏢 Scotiabank
📍 Toronto