Top AWS Jobs in Toronto

Lead a small engineering team to design, build, and operate PlanHub's email delivery platform. Own architecture, cloud-native infrastructure (AWS, Terraform/OpenTofu, ECS), observability, reliability, and AI-assisted development practices. Mentor engineers, partner with product and infra teams, and drive scalable, fault-tolerant systems to support critical transactional email workflows and business needs.

Lead application migration and modernization initiatives to AWS, utilizing cloud-native practices and providing technical leadership for development teams.

Build and operate the core infrastructure for Arena's online evaluation systems: design low-latency, high-reliability APIs and gateways, implement enterprise-grade features (rate limiting, auth, metering, audit logging), instrument observability (tracing, latency, usage tracking), integrate with LLM providers and the evaluation platform, and collaborate with research and product teams to scale and harden systems for bursty, unpredictable traffic.

Lead a team of developers to architect and scale Node.js and Salesforce products, improve developer velocity, and enhance solution performance.

As a DevOps Engineer, you will design, develop, and deploy scalable SaaS solutions, automate infrastructure tasks, and collaborate on CI/CD enhancements.

As an AI-Driven Full Stack Engineer, you'll design and implement features for an AI-powered web application, working across the stack and integrating AI models to transform insurance processes.

As a Junior Software Engineer, you will develop full stack features for an AI-powered web application, integrating AI models and collaborating with senior engineers. Responsibilities include building backend services and creating user experiences while participating in design discussions and code reviews.

The DLP Solutions Architect will own technical presales efforts for Cyera's DLP product, providing technical expertise, crafting solutions, and building customer relationships while supporting product management and engineering teams.

As a Senior Software Engineer, you will develop core data pipeline components for an AI-native data warehouse, oversee feature delivery, and ensure data quality and reliability.

Design, build, and operate production AI systems, enhance backend services, improve reliability, and collaborate on technical projects within the AI-native engineering team.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

As a Staff Software Engineer at Juniper Square, you'll lead architectural decisions and develop AI-powered systems, mentoring engineers and ensuring high-quality technical standards while collaborating with cross-functional teams.

The Senior Mobile Developer will build and maintain mobile applications using React Native and GraphQL, mentor teammates, and ensure quality in software development.

Develop and maintain server-side components for Tempo's flagship Jira Cloud products using Kotlin/Java. Design scalable distributed systems and APIs, write unit/integration/performance tests, optimize performance and database queries, collaborate with product, design, QA and docs teams, and contribute to code reviews with a focus on security, UX, and maintainability.

As a Full Stack Developer, you will design and maintain scalable applications, collaborate with teams, implement best practices, and mentor junior developers.

The Infrastructure Engineer designs and maintains distributed systems, writes backend services in TypeScript, and operates cloud infrastructure, ensuring reliability and scalability.

As a Site Reliability Engineer, you'll enhance system reliability, collaborate on production readiness, define SLIs/SLOs, and improve incident response.

As a Staff Backend Engineer, you'll develop and maintain scalable reconciliation systems within Grafana Cloud, enhancing reliability and operational efficiency while collaborating with multiple teams.

Conduct penetration tests and security assessments on IoT, ICS, and automotive systems, providing actionable insights and risk mitigation guidance for clients.

Executive leader responsible for strategy, modernization, delivery, governance, and vendor management of enterprise platforms (ERP, HCM, EPM, Finance, HR, Procurement). Leads transformation, cloud adoption, integration, AI enablement, portfolio governance, and cross-functional stakeholder engagement to drive operational excellence and business value.

Lead architecture, design, and delivery of scalable full-stack cloud-native applications. Mentor engineers, drive technical strategy, build reusable services, improve performance and reliability, and collaborate with product and stakeholders to deliver business-critical solutions.

Lead vision, strategy, and execution for the Elastic Agent Builder to enable scalable context for AI agents. Engage enterprise customers and sales to capture requirements, define roadmap for context engineering, benchmark agent capabilities with data science, design UX for context refinement, and evangelize capabilities to partners and the developer community.

Lead global SRE team to design, operate, and optimize scalable cloud infrastructure (AWS/Azure/GCP). Own reliability, observability, incident response, IaC, CI/CD, cost optimization (FinOps), security hygiene, and mentor engineers while contributing hands-on and researching AI-driven SRE tooling.

Build and maintain backend and full-stack marketplace features while supporting ML Ops infrastructure (model deployment, feature stores, real-time pipelines, monitoring). Collaborate with data scientists to bring models to production, write well-tested code, address performance and scalability issues, and contribute to technical planning and cross-functional communication.

Build and maintain full-stack marketplace features and support ML Ops infrastructure (model deployment, feature stores, real-time pipelines, monitoring) on Chalk and Vertex AI. Collaborate with data scientists to productionize models, write well-tested code, address performance/scalability issues, and contribute to technical planning.