Top AWS Jobs in Toronto

Own and operate infrastructure for a large-scale sports betting and media platform across cloud and production environments. Lead infrastructure migrations, build Kubernetes platform tooling and CI/CD automation, improve observability and incident response, support development teams, troubleshoot distributed systems, reduce operational toil, and mentor engineers.

Designs and maintains scalable test automation frameworks using Java, Python, and Playwright. Performs functional, API, integration, database, migration, performance, security, and accessibility testing. Validates Snowflake data, ETL processes, transactions, and business rules with complex SQL. Integrates tests into CI/CD pipelines and uses generative AI tools to improve testing productivity and coverage. Establishes AI testing governance, analyzes defects, mentors junior engineers, and drives quality engineering improvements.

Design, build, and deploy GenAI and agent-based systems for Wealth Management. Lead end-to-end solution development, integrate AI with existing platforms, enforce MLOps, model governance, security, and regulatory compliance, and collaborate with cross-functional teams to drive production-grade, scalable AI products.

Define and evolve Interac’s enterprise data architecture strategy, target-state blueprints, transition roadmaps, governance standards, and reference architectures. Establish guardrails for data quality, lineage, metadata, ownership, access, retention, privacy, security, and regulatory compliance. Lead architecture reviews and risk assessments across warehouse and lakehouse environments, while guiding scalable integration, semantic modeling, data products, and analytics and AI enablement across cloud, SaaS, and on-premises platforms.

Provides technical support, troubleshooting, maintenance, and development for applications, databases, ETL workflows, APIs, and internal websites. Responsibilities include database optimization, monitoring, preventive maintenance, QA, user support, documentation, reporting, data integration, JavaScript automation, and DevOps improvements. Collaborates with stakeholders and developers to resolve issues, enhance reliability, prevent fraud, and automate processes.

Leads architecture and hands-on development of scalable, cloud-native full-stack applications using Java, Spring Boot, GCP, microservices, and big data technologies. Manages cross-functional engineering teams, mentors staff, establishes technical standards, and oversees secure software development, reliability KPIs, documentation, releases, and cloud optimization. Develops APIs, prototypes solutions, supports infrastructure-as-code, and collaborates with product, architecture, SRE, and business stakeholders.

Lead reliability engineering for AWS and Kubernetes-based systems. Build secure CI/CD pipelines, improve observability, define SLOs, optimize distributed systems, manage incidents, and strengthen platform resilience. Partner with engineering, security, platform, and product teams while mentoring engineers and reducing operational toil through automation and developer tooling.

Develop, train, deploy, and optimize machine learning models for research and production ultrasound applications. Build scalable ML data pipelines and tools, automate retraining, evaluation, and monitoring, and improve inference speed, robustness, and maintainability. Collaborate with researchers and software engineers to productionize ML research while reducing technical debt and communicating concepts to technical audiences.

Owns complex Tier 2 and Tier 3 customer support issues for SaaS products, using SQL, logs, sandboxes, and cloud infrastructure knowledge to troubleshoot and resolve problems. Builds customer relationships, documents cases in Zendesk, coordinates with Development, QA, Implementation, and Product teams, mentors junior support staff, contributes to knowledge-base content, and improves support processes. The role also supports implementation-to-production transitions and applies AI tools to enhance support workflows.

Leads delivery of medium- and large-scale AWS digital transformation programs, overseeing planning, execution, reporting, risk mitigation, quality, customer outcomes, and continuous improvement. Manages multi-functional teams of business analysts and engineers, develops product and service roadmaps, identifies business opportunities, resolves customer issues, and coaches, recruits, and develops staff. Requires strong program management, client service, agile delivery, business analysis, communication, and team leadership experience.

Designs, secures, operates, and supports multi-account cloud infrastructure across AWS, Azure, and GCP. Responsibilities include AWS networking, Terraform infrastructure as code, GitHub Actions CI/CD pipelines, identity and access management, cloud governance, observability, incident response, disaster recovery, cost optimization, and compliance controls. The role also develops automation, maintains technical documentation, and provides after-hours support when needed.

Owns end-to-end cloud operations for a multi-region SaaS portfolio, ensuring availability, performance, reliability, and cost efficiency. Leads production availability incidents, triage, resolution, root cause analysis, configuration and change management, monitoring, and alerting. Builds and develops a team of system administrators and SREs while partnering with Development, Technical Security, and Support to improve operational readiness and accountability across AWS and Azure environments.

Build and own ML infrastructure for distributed training, inference, experiment tracking, model registries, and CI/CD. Enable active-learning and closed-loop optimization, collaborate with computational scientists, and mentor colleagues to translate research prototypes to production-grade systems.

Develop full-stack features for an AI-powered web application using Python, React, Redux, PostgreSQL, and AWS. Integrate AI models and APIs for document processing, data extraction, and recommendations; build scalable backend services and intuitive interfaces. Participate in architecture planning, code reviews, release planning, cross-team initiatives, and AI experimentation. Collaborate with senior engineers, QA, and other teams while taking increasing ownership of feature development.

Design and maintain reusable Terraform modules and CI/CD frameworks (GitHub Actions) integrating security scanning (Snyk). Architect resilient, cost-effective AWS infrastructure, enable observability, define standards for developer self-service, mentor junior engineers, and collaborate with SRE, security, and application teams.

Build high-performance API services and production-grade Generative AI systems. Design and implement end-to-end RAG pipelines, vector stores, embeddings, and latency-optimized generators. Develop agentic AI using LangChain/CrewAI/Semantic Kernel, integrate LLM APIs and AWS Bedrock, manage CI/CD and ML pipelines, and apply evaluation frameworks to detect hallucinations and optimize performance.

Design, build, and scale resilient distributed payment systems handling 1,000+ transactions per second. Collaborate with Product, Revenue Operations, Cloud Platform, and Security teams to shape product requirements and roadmaps. Lead AI-augmented software delivery, code reviews, testing, observability, performance optimization, incident response, on-call rotations, and root cause analysis while maintaining strict security, reliability, and low-latency standards.

Lead design and delivery of reliability projects for Coinbase's platform: secure service configuration and secrets management, improve canary-based deployments, partner with core services to increase scalability and reduce incidents, drive reliability best practices, and participate in on-call rotations.

As a Senior Software Engineer, you will design and build a new lifecycle orchestrator service, mentor engineers, and drive technical strategies while improving engineering standards and processes.

Senior client-facing Sales Engineer for IIoT platform sales in manufacturing. Perform technical discovery, design custom solutions and demos, run pilots, support RFIs/RFPs, liaise with product teams, assist resellers, and attend customer meetings and conferences to translate factory-floor challenges into Litmus platform value.

Work with prospects and customers to design, configure, and implement Litmus Edge and Litmus Edge Manager in proofs-of-concept and production. Lead implementations, provide L3/L4 support, create best-practice content, assist sales with technical proposals, and deliver partner and customer-facing demos and training.

Build and operate full-stack services for non-human identity governance across cloud and on-premises environments. Responsibilities include developing APIs, backend services, data pipelines, and occasional UI features; owning features through production; participating in design and code reviews; resolving reliability issues; applying secure development, testing, and observability practices; and mentoring engineers.

Leads finance transformation for hyperscaler marketplace operations, designing scalable financial systems, automating marketplace workflows, integrating AWS, GCP, and Azure platforms, and building transaction data pipelines. Oversees revenue recognition, ASC 606 compliance, reconciliations, billing integrity, and marketplace fee tracking. Partners across Finance, Sales Operations, Product, Engineering, and IT while managing UAT, change initiatives, and SOP development for new marketplace capabilities.

Design, build, test, and support data and AI products by developing ETL/ELT pipelines, data models, and automation. Partner with stakeholders to translate requirements, perform data profiling and regression testing, troubleshoot production issues, and contribute to technical designs and process improvements to accelerate delivery.

Design, build, test, and support data and AI products. Translate business requirements into data solutions, contribute to technical design, develop reusable frameworks and automation, perform ETL/ELT development and testing, conduct regression testing and root-cause analysis, and drive process improvements for delivery and deployment.