Top AWS Jobs in Toronto

Build Clutch's Internal Developer Platform and CI/CD systems, define platform strategy and standards, design and scale AWS/Terraform infrastructure, improve developer velocity via automation, tooling, observability, and reusable infrastructure patterns to enable dozens of engineering teams.

Productionize, optimize, and scale LLM and ML inference across multi-cloud and Kubernetes. Deploy GPU-based workloads, implement routing/failover for model services, reduce latency via quantization/pruning/distillation, profile and tune hardware utilization, and build observability, monitoring, and cloud-native guardrails for enterprise AI services.

Senior DevOps / Site Reliability Engineer to build, operate, monitor, and scale an enterprise AI platform on Azure. Responsibilities include Azure infrastructure and Kubernetes deployment, IaC and CI/CD automation, advanced dashboards and observability, monitoring/alerting, capacity planning and automated scaling, troubleshooting, and collaborating with developers and AI engineers. Hybrid role based in the GTA with occasional client travel.

This role involves serving as the primary technical advisor for enterprise clients, ensuring effective implementation of low-code platform solutions, providing proactive technical support, and facilitating knowledge transfer to enhance client self-sufficiency.

Lead design and operation of scalable AWS/GCP cloud infrastructure. Build and operate Kubernetes (EKS), Docker, Terraform/Terragrunt, Helm and GitOps workflows. Improve CI/CD with GitHub Actions and ArgoCD, implement monitoring and observability, strengthen security, disaster recovery, and developer self-service automation to improve platform reliability and productivity.

Senior-level infrastructure analyst responsible for monitoring, troubleshooting, and maintaining core network routing, perimeter firewalls, multi-cloud environments (Azure/AWS/GCP), virtualization and HCI platforms, and enterprise endpoint services using Microsoft 365 and Intune. Acts as Tier 3 escalation for service desk, automates tasks with PowerShell/Bash/Python, and supports cross-team operational priorities.

Design and architect scalable, secure cloud solutions by analyzing complex requirements, selecting and integrating technologies, producing technical documentation, leading stakeholder presentations, collaborating with development teams for implementation, mentoring junior architects, and continuously evaluating emerging technologies for optimization and compliance.

Design, deploy, and maintain HPC and MLOps infrastructure across cloud and on-prem clusters. Manage schedulers (Slurm/PBS), optimize MPI/CUDA stacks, storage and networking, automate deployments with Python/Bash, instrument systems, and enable AI training/inference pipelines while collaborating with product and support teams.

Lead product development of AI/ML bioinformatics workflows (ML Ops, generative AI for protein design/folding). Define roadmap, gather/prioritize scientific requirements, manage agile delivery with data and platform engineers, track post-launch impact, and align stakeholders to drive R&D AI product strategy and continuous improvement.

Design and implement data models, pipelines, and ML systems to power AI agents and analytics. Build, deploy, and monitor machine learning models at scale, integrate Snowflake/AWS and Salesforce Data Cloud, and deliver production-ready data products and views to stakeholders.

Join Zip's Core Infrastructure team to design, build, and operate global multi-region architectures. Own infrastructure components such as Kubernetes, AI infra, observability, deployment pipelines, and cost optimization. Collaborate with engineering teams to ensure scalable, reliable systems and support Zip's product roadmap.

Lead technical design, enhancement, and support of Ab Initio ETL applications; architect and migrate ETL/ELT pipelines to AWS (S3, Glue, Redshift, Lambda); drive performance, governance, and CI/CD; operate in Agile/Scrum or SAFe using Jira; mentor engineers and coordinate cross-functional delivery while ensuring stability of existing platforms.

Build responsive web applications and scalable frontend/backend services, design secure APIs and databases, implement AI-powered search and asset management features, collaborate on system architecture, and optimize performance and UX for a cloud-native DAM platform.

Manage and coach an EngOps Applications team responsible for infrastructure and operational health. Own planning, delivery, reliability, incident response, technical oversight, runbooks, and cross-team accountability for production systems.

The Senior Data Scientist will develop ML and AI algorithms to drive business value, manage data pipelines, and communicate insights with stakeholders.

Own customer communication and manage full project lifecycle for AWS cloud engagements. Run kickoffs, track work in Jira, manage budgets, timelines, KPIs, timesheets, resource allocation, risk register, scope changes, and retrospectives to ensure on-time, on-budget delivery and high CSAT.

Design, build, test, deploy, and maintain scalable full‑stack web applications. Create responsive React frontends and Java/Spring Boot backend services on AWS. Develop RESTful APIs, database integrations, automated tests, CI/CD pipelines, and monitor performance. Collaborate with product, design, and architecture teams, participate in code reviews, write technical designs, mentor junior engineers, and apply secure, accessible, and performant engineering practices.

Develop, test, and maintain marketplace applications using C#, .NET, Java, React and TypeScript. Write unit tests, participate in code reviews, debug production issues, support level-3 incidents, and collaborate with product and engineering teams. Continuously learn new tools (cloud, containers, AI) and follow engineering standards and automation best practices.

Design and build end-to-end, enterprise-grade systems that enable AI agents to initiate and complete finance workflows. Own features across backend and frontend, integrate AI/ML models into auditable production systems, ensure scale, security, and reliability, and collaborate with product and customers to solve accounting problems.

Design, build, and operate secure, tenant-isolated cloud infrastructure and CI/CD for an AI-native multi-tenant platform. Implement observability, policy-as-code, SLAs, incident response, and automate provisioning (Terraform/Helm). Support deployment, monitoring, and secure operations for ML/agent systems at scale.

Founding full-stack engineer to architect and build a production platform combining large-scale data systems and AI-native agents. Work across backend, frontend, data pipelines, agents, and deployment systems; define architecture, devops, CI/CD, and early engineering processes while shipping features and growing the team.

The Senior Software Developer will lead design and implementation of backend systems, mentor peers, and enhance AI capabilities in tax research software, focusing on high-quality standards and rapid delivery.

As a Senior Machine Learning Engineer, you will design, develop, and deploy ML systems, mentor team members, and collaborate on advanced AI applications in tax research.

As a Software Developer II, you will design and implement software systems, collaborate with peers, and improve product capabilities using various technologies, particularly TypeScript and Python.

The Cloud Software Engineer will design distributed systems for observability, ensuring reliability and performance, while automating operational work and collaborating with teams.