Top AWS Jobs in Toronto

Lead and build a platform engineering team that delivers developer experience: CI/CD, deployment automation, observability, test infrastructure, and AI-assisted tooling. Own roadmap, metrics (DORA/DevEx), hiring and coaching, partner cross-functionally to drive continuous deployment, quality, and incident management, and ship high-leverage platform capabilities for product engineering squads.

Senior backend engineer to architect and implement distributed, cloud-native backend services and public APIs that ingest and normalize high-volume IoT/sensor data. Lead design and deployment of resilient ingestion pipelines, workflow orchestration, authentication, and monitoring in AWS. Interface with enterprise clients, shape product and architecture, and drive engineering standards and automation.

Build end-to-end features for an agentic AI media manager: design APIs, backend services, agent logic, data models, and customer-facing interfaces; use AI coding tools, test and operate production systems, work directly with customers, and iterate on agent reliability, guardrails, and human approval flows.

Lead full‑stack architecture and technical vision for enterprise systems while architecting and orchestrating agentic, AI-native delivery. Design APIs, services, data pipelines, cloud infrastructure, and integrations with LLMs, RAG, vector stores, and composable platforms. Mentor engineers, drive spec-driven agent workflows, and collaborate with cross-functional stakeholders to deliver production-ready, scalable solutions.

Lead design and delivery of the integrations platform supporting 250+ integrations. Build APIs, integrations, tooling, and observability; engage customers; optimize performance and scalability; set architectural direction and best practices.

Design, build, and maintain CI/CD pipelines, developer platform tooling, and IaC for a large Nx monorepo. Improve release safety, observability, and reliability; support Kubernetes deployments, GitOps flows, and platform security; coach teams on DevOps best practices and developer experience.

Lead and manage a team of technical support professionals delivering AWS support, driving operational excellence and enhancing customer satisfaction through AI and data-driven strategies.

As an AI/ML DevOps Engineer, you will operationalize AI solutions, build CI/CD pipelines, and ensure production system reliability. Collaborate with data scientists and engineers to deliver AI capabilities and maintain strong operational practices.

Senior backend engineer responsible for building and owning APIs and partner integrations, optimizing database and service performance, debugging production issues using observability (logs, metrics, traces), mentoring engineers, and guiding architecture and scalability decisions while shipping reliable Python/Django services.

The role involves designing and developing front-end and back-end components, mentoring team members, ensuring system efficiency, and optimizing platform performance in a collaborative team environment.

Design, implement, and maintain high-performance SBT Content microservices for P&C insurance. Collaborate in agile teams, apply AI-assisted coding, ensure test coverage, CI/CD, observability, and scalable cloud deployments.

Lead design and implementation of scalable backend services and frontend features across a polyglot stack. Drive architecture, API design, testing, CI/CD, observability, and operational excellence. Use AI tools extensively to generate, test, debug, and document code. Mentor engineers, conduct reviews, participate in on-call rotations, and collaborate cross-functionally to deliver reliable, high-performance dealer-facing SaaS solutions on AWS.

Lead rapid concept-to-production work using AI design tools and modern full-stack frameworks. Build accessible, performant frontends and robust backends, implement APIs, auth, caching, and databases, and collaborate with designers and AI builders to maintain design systems and deliver production-ready applications.

Join a small team to improve a tech product aimed at upskilling users in MENA, working with JavaScript and Node.js in a collaborative remote environment.

Develop scalable web applications using React and Next.js, implement backend solutions in Python, maintain DevOps practices, and collaborate with AI/ML teams to deploy applications.

The Guidewire Data Engineer will design schemas in Snowflake, develop ETL processes, optimize SQL queries, and integrate Guidewire with data platforms.

Build scalable backend systems, develop LLM agents, and ensure fast adaptation in a dynamic environment at Sentra.

The Backend Software Engineer will develop and maintain backend systems for data processing related to coffee farming, utilizing Python and PostgreSQL. Responsibilities include feature development, problem-solving, and adapting systems to regulatory changes while ensuring system resilience.

As a backend engineer, you will design and develop healthcare APIs, leverage AWS services, and enhance existing systems while ensuring high-quality standards.

Lead end-to-end full-stack engineering initiatives for Project Simulation and Asset Operations. Build scalable frontend and backend systems, ensure code quality, collaborate cross-functionally, debug production issues, and participate in on-call rotation.

Lead end-to-end engineering initiatives for customer-facing features in a fast-paced startup. Build and maintain backend and frontend systems, design and evolve GraphQL APIs, debug production issues, participate in on-call rotation, and collaborate cross-functionally with product, policy, and commercial teams to deliver high-quality, scalable software for battery asset operations and project simulation.

The Infrastructure Engineer will design and implement advanced cloud infrastructure, manage Kubernetes, establish engineering standards, and support IoT deployments in manufacturing environments while driving automation and mentoring teammates.

The Edge Functions Engineer will evolve the Supabase Edge Runtime, implement monitoring and optimizations, manage features, and work closely with the Deno open-source teams.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

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.