Top AWS Jobs in Toronto

The Enterprise Architect will lead infrastructure and application modernization, guide solution architecture practices, enforce standards, and manage technical debt across the organization.

As a Senior Data Implementation Engineer, you will oversee complex customer implementations, build automated ETL workflows, define data validation frameworks, and mentor junior engineers while ensuring compliance with data security regulations.

Lead complex, enterprise data implementations end-to-end, act as technical escalation, design scalable ingestion/onboarding solutions, establish playbooks and tooling, drive automation, mentor implementation engineers, and represent ODAIA with customers.

Lead a team of engineers in developing AI-driven products, balancing people management and hands-on technical guidance, and ensuring project and architectural success.

This role involves managing a team of engineers, guiding architectural decisions, and ensuring successful project execution for AI/ML-driven software products.

Develop and deploy models for the Piai claims-intelligence platform using machine learning, NLP techniques, and collaboration with various teams.

The Senior DevOps Engineer will manage AWS infrastructure, develop infrastructure as code using Terraform, support deployment processes, and improve observability in cloud environments, collaborating with engineering teams.

Design and develop scalable software applications, implement automated testing, mentor junior developers, and optimize performance in a remote environment.

The Sr Cloud Engineer designs and manages cloud infrastructure, ensuring security and efficiency while collaborating across teams and optimizing resources.

Lead a data science team to develop machine learning models and advanced analytics for customer engagement, pricing, and loyalty programs, while collaborating across business units to drive insights and improvements.

As a Junior Data Engineer, you will develop data pipelines on Databricks, optimize ETL processes, and collaborate with stakeholders to transform data into insights within a cloud environment.

As a Senior QA Engineer, you will ensure quality in software for financial services through automated and manual testing, participating actively in Agile team processes.

Develop and execute test plans and automated testing, mentor junior QA engineers, and ensure software meets quality standards and customer requirements.

The Senior Data Scientist will develop growth strategies, build predictive models, and foster a data-driven culture while leveraging expertise in ML and statistical analysis.

Lead and mentor a software development team focusing on cloud data platform components. Drive business initiatives, enhance engineering practices, and ensure project delivery. Collaborate across teams to provide real-time data-centric experiences.

This role involves product development, solution design, and architecture in a fast-paced environment, emphasizing modern UI and backend development skills.

The Staff Application Engineer will develop critical application features, ensure code quality, and work collaboratively to impact sales compensation solutions.

As a Staff Backend Engineer, you will develop complex backend solutions, focusing on the Spark-based data platform while ensuring code quality and collaborating closely with teams.

As a DevOps Specialist, you'll maintain cloud infrastructure, optimize CI/CD pipelines, manage Kubernetes clusters, enhance observability, and collaborate with product teams.

Lead the development of Java-based microservices within the Core Payment team while collaborating with various stakeholders and ensuring code quality. Manage project scopes, solve production issues, and mentor junior developers.

Build and maintain the Kotlin backend: deliver core features, design and build APIs for web and mobile, write integration tests, share product ownership, and help improve customer experience.

The Database Engineer will design, implement, and manage high-performance databases, ensuring data integrity and security while collaborating with teams to improve the data infrastructure.

Lead design, development, and production deployment of AI/ML capabilities for a commercial real estate SaaS platform. Build LLM-powered features and custom models, establish AI standards and infrastructure, mentor engineers, drive applied research, and partner with product, data, and engineering teams to deliver scalable, responsible AI solutions.

Design, build, and optimize cloud-based data platform components: ingest and transform varied datasets, create metadata-driven pipelines and data APIs, support AI/ML infrastructure, implement monitoring and metrics, and improve data processes to enable analytics and operational systems.

Build and maintain platform and infrastructure systems across the stack: cloud infrastructure, IaC, CI/CD, queues, observability, auth, and developer experience to improve reliability and developer velocity.