Top AWS Jobs in Toronto

Design, build, and deploy scalable AI/ML solutions: end-to-end pipelines, fine-tune LLMs, production model deployment with CI/CD, serve models via microservices/APIs, monitor model performance, collaborate with data/cloud teams, and prototype/evaluate new AI frameworks using Python, SQL, Spark and MLOps tools.

Build and maintain cloud-native services, APIs, and platform capabilities. Design, implement, test, and troubleshoot scalable SaaS/backend systems. Collaborate with product, UX, and engineering teams, participate in code reviews, agile delivery, and continuous learning.

Use customer, digital, and transportation data to build targeting, propensity, pricing, loyalty, and churn models; run experiments (A/B), optimize promotions and pricing, present insights to stakeholders, manage data structures in Databricks/AWS, and lead project work with business partners to drive data-driven decisions.

Build end-to-end features for Faire's Brand pillar, collaborating with product, design, and data. Work across backend, frontend, and mobile stacks to optimize performance and scalability, mentor engineers, and drive product improvements from discovery through implementation while using modern tooling and AI productivity aids.

The Staff Software Developer will lead design and implementation of features, mentor junior engineers, and create scalable geospatial solutions using the ArcGIS stack.

Lead design, develop, deploy and maintain Java-based REST APIs and microservices using Spring Boot, Docker and Kubernetes. Build event-driven services with Kafka, improve CI/CD pipelines, debug/resolve defects, mentor colleagues, and support legacy APIs and integrations.

Lead and own a broad domain end-to-end: set multi-team architecture and roadmap, build platform and tooling, ship production systems, define AI standards and evals, partner with product/design/data, coach senior engineers, and solve high-impact technical and product problems.

Own end-to-end engineering problems across Babylist's Rails monolith and AI-enabled systems. Design, ship, and iterate on features and abstractions, run experiments, harden critical paths, review risky changes, and share AI learnings. Work across backend, frontend, mobile, data and ML infrastructure to improve customer outcomes and platform reliability.

Lead end-to-end technical client engagements: discovery, architecture, prototyping, and delivery of AI-enabled solutions. Design system architectures and integrations, analyze client data sources, build proofs-of-concept, guide engineering teams, run workshops, and mentor junior developers and Fellows to deliver production-ready outputs.

Design, build, deploy, and own high-performance, scalable data-platform components for streaming analytics, reporting, and ML. Collaborate with cross-functional teams, perform design/code reviews and performance tuning, debug production incidents, participate in on-call rotation, and mentor engineers to scale the organization.

Lead a globally distributed team of 10 engineers owning runtime foundations (Kubernetes, service mesh, Vault, Kafka). Drive quarterly priorities, coordinate cross-functional work, mentor engineers, manage on-call responsibilities, improve reliability, and communicate risks and trade-offs to stakeholders.

Design, build, and deploy machine learning and deep learning models; integrate AI into customer-facing applications; run experiments, preprocess data, and maintain training/evaluation pipelines; optimize model performance and scalability; stay current with research and contribute to system design and code reviews.

Lead the development of AI-powered solutions, drive technical strategy and innovation, mentor engineers, and ensure quality and operational excellence.

Design and document solution and information architectures for client engagements, drive technical design reviews, support sales and project estimating, ensure quality implementation, conduct code reviews, and create reusable delivery assets focused on automation and cloud-native solutions.

Lead design, architecture, and delivery of enterprise-scale data platforms using Databricks and Spark. Architect Lakehouse solutions, build ETL/ELT pipelines, implement IaC and CI/CD, ensure data governance and security, mentor engineers, and partner with Fortune 500 clients from discovery through production.

Site Reliability Engineers apply software and systems engineering to improve reliability, performance, and operability. They deploy, configure, monitor, recover, and scale services, participate in on-call rotations, evaluate products before and after releases, and spend at least half their time engineering away problems while collaborating with teammates.

Lead enterprise data governance, policy, and resiliency programs. Define classification, retention, backup, immutability, and DR standards; translate policy into technical controls; design/operate backup and recovery across hybrid environments; lead DR exercises, testing, and audits; monitor compliance and drive continuous improvement; advise cross-functional stakeholders on data protection and resiliency strategies.

Lead design, implement, and maintain a scalable SaaS insurance platform across front-end and back-end. Provide technical direction, mentor developers, enforce best practices, optimize performance, ensure security and compliance, and drive adoption of modern architectures and testing methodologies.

Lead migration of CI/CD deployment pipelines from IBM UrbanCode Deploy to Octopus Deploy; refactor Groovy scripts into Octopus/C# automation; design, test, and production-enable release automation for VM and mainframe platforms; collaborate with development, infrastructure and release teams; troubleshoot deployments and drive CI/CD governance, security, and continuous improvement.

Lead design and migration of enterprise CI/CD pipelines from IBM UrbanCode Deploy to Octopus Deploy, refactor Groovy scripts into Octopus/C# automation, validate pipelines through testing and production enablement, troubleshoot deployments across VM and mainframe environments, and drive CI/CD governance, security, and continuous improvement.

Design and implement secure, scalable end-to-end IoT and edge solutions using AWS or Azure. Build fault-tolerant, high-availability cloud and edge systems, create architecture and design documentation, collaborate with cross-functional teams (data, cybersecurity), mentor developers, and guide technical direction while keeping current with IoT and cloud trends.

Lead development and governance of enterprise AI architecture, defining reusable AI services, patterns, and reference architectures. Drive architecture reviews and approvals, partner with business and risk teams to translate requirements into scalable, compliant AI solutions, and support implementation teams while ensuring responsible AI, security, and regulatory alignment.

The Software Engineer will design and deliver software solutions for research workflows, ensure system scalability, and collaborate with cross-functional teams.

Design and deliver software solutions, ensuring system scalability and reliability, while collaborating with various stakeholders to enhance data analysis and research workflows.

The Software Engineer is responsible for designing and delivering software solutions, ensuring system scalability, and contributing to technical vision and best practices.