Jobs / Scotiabank
Senior AI Platform Engineer
Scotiabank · Toronto, ON, Canada
Toronto, ON, CanadaExp: 5+ yrsOnsite
Remuneration
Competitive rewards including a bonus, flexible vacation, personal and sick days, and benefits starting on day one.
Location
Toronto, ON, Canada
Visa sponsorship
Not specified
Job summary
Leads the design, development, and operation of scalable enterprise platforms for building, deploying, monitoring, and governing production AI and machine-learning solutions. The role provides technical leadership across cloud infrastructure, MLOps, LLMOps, and generative AI, delivering reusable APIs and developer tooling, Kubernetes-based services, and reliable, secure platform capabilities. It also establishes engineering standards, supports production operations, and mentors engineers.
Benefits
Online courses, cross-functional development opportunities, and tuition assistanBonus, flexible vacation, personal and sick days, and benefits starting on day oCommunity engagement programs
Qualifications
- Bachelor’s degree in a relevant technical discipline or equivalent practical experience.
- At least five years of professional software engineering experience, including designing and delivering production platforms, APIs, or distributed systems.
- Advanced programming skills in Python, Java, Scala, Go, or a similar language.
- Experience designing scalable, highly available services, including APIs, asynchronous processing, distributed systems, data stores, caching, and performance optimization.
- Hands-on experience with Azure, AWS, or Google Cloud.
- Experience with Docker, Kubernetes, infrastructure as code, CI/CD, release automation, and production operations.
- Experience implementing MLOps or LLMOps capabilities, such as model deployment, experiment tracking, registries, automated evaluation, observability, and lifecycle controls.
- Knowledge of machine-learning systems, data and feature pipelines, model serving, generative AI patterns, and production AI risks.
- Experience building front-end applications using React, Angular, or Vue.
- Experience applying secure development practices, identity and access controls, secrets management, and threat mitigation.
- Technical leadership, communication, collaboration, problem-solving, and mentoring skills.
Responsibilities
- Lead the architecture, design, development, and evolution of reusable AI and machine-learning platform services.
- Design scalable APIs, orchestration layers, SDKs, developer portals, and self-service tools.
- Implement production MLOps and LLMOps patterns, including CI/CD, versioning, evaluation, observability, drift detection, and release controls.
- Design and operate resilient cloud-native and containerized services using Kubernetes, Docker, managed cloud services, and infrastructure as code.
- Guide generative AI platform capabilities, including model serving, retrieval-augmented generation, vector search, agent workflows, evaluation, and guardrails.
- Build reliability, security, privacy, governance, auditability, and cost optimization into platform architecture and engineering practices.
- Establish standards for code quality, testing, observability, documentation, API design, operational readiness, and production support.
- Lead technical reviews and evaluate platform technologies and adoption decisions.
- Mentor engineers and provide hands-on technical guidance.
- Lead incident response, root-cause analysis, performance optimization, and continuous improvement for critical platform services.
Skills
AirflowArgo WorkflowsArgo CDARM TemplatesAWSAzureBicepCloudFormationDatabricksDockerGCPGoHelmJavaKubernetesPulumiPythonScalaSparkTerraform
Certifications
Azure AI Engineer AssociateAWS Certified Machine Learning EngineerGoogle Professional Machine Learning EngineerCertified Kubernetes Administrator
Degrees
Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, M
Industry
BankingFinancial services
Relocation
No