Senior AI Engineer

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 strong 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, 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.
• Lead 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.
• Design and implement automated ML/LLM delivery pipelines covering training, evaluation, approval, deployment, and rollback.
• Establish 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.

Interested?

If your experience is closely related but doesn’t align perfectly with every qualification, we do encourage you to apply - you might be the right candidate for this or other roles at Scotiabank!