Top AWS Jobs in Toronto

Develop and maintain infrastructure, automation, and CI/CD pipelines for building, testing, deploying, validating, and evaluating Cerebras software across cloud and datacenter environments. Create Python and shell tools, manage Docker and Kubernetes environments, support AWS-based services, and troubleshoot software quality and performance issues.

Staff Product Engineer responsible for executing complex features across multiple teams and technology stacks, including backend, frontend, and mobile. Collaborates with product, design, marketing, and data partners; optimizes scalable web applications; contributes to product strategy; and mentors engineers on technical and product judgment. The role supports Brand pillar priorities, drives improvements end to end, and promotes maintainable, high-quality software development.

Lead frontend engineer responsible for designing, building, and supporting Agilent.com experience-layer capabilities using AEM, DA.live, EDS, and Adobe Forms. Deliver reusable DA.live Blocks, integrate with content/catalog/personalization services, ensure performance, accessibility, SEO, and global scale. Act as technical product owner within a POD, mentor engineers, participate in agile delivery, CI/CD, testing, and production support.

Leads strategy, engineering, operations, security, compliance, and lifecycle management for Four Seasons’ web, eCommerce, and digital experience platforms. Oversees platform roadmaps, cloud architecture, DevOps, SRE, observability, releases, incident management, AI-enabled capabilities, vendor relationships, and regulatory requirements. Builds and develops technical teams while partnering with marketing, analytics, QA, security, legal, privacy, and business stakeholders to deliver reliable, secure, high-performing guest-facing digital experiences.

Develop and maintain full-stack coaching applications across web and mobile platforms. Build React frontends, Python and AWS-backed APIs, and support React Native iOS applications. Apply testing, automation, DevOps, security, documentation, and AI-assisted development practices. Collaborate with infrastructure and engineering teams on integrations, technical planning, sizing, and project delivery from requirements through launch.

Designs, evaluates, and maintains predictive statistical and machine learning models for player evaluation, acquisition, tactical simulation, and performance optimization. Analyzes spatio-temporal tracking data, conducts quantitative research, audits and backtests models, and partners with data engineering teams on scalable pipelines and deployment. Communicates probabilistic insights through visualizations and executive briefs for coaches, scouts, and sports leadership.

Design and build Samsara’s cloud governance platform, including IAM guardrails, security controls, compliance automation, and software supply-chain security tooling across AWS and GCP. Develop reliable distributed systems, secure CI/CD patterns, and SAST/DAST capabilities. Contribute to technical roadmaps, collaborate across infrastructure, security, compliance, and engineering teams, and communicate design tradeoffs while mentoring teammates through reviews and pairing.

Lead and manage full software development lifecycle for front- and back-end platforms. Design architecture, optimize performance and scalability, oversee deployments, testing, maintenance, and cross-platform compatibility. Mentor and grow development teams, coordinate with stakeholders, enforce risk and compliance practices, and drive continuous improvement while fostering inclusion and collaboration across functions.

Design, develop, and implement secure, scalable full-stack software solutions for financial services clients. Translate business requirements into technical specifications, build front- and back-end applications, conduct code reviews, mentor junior engineers, and support testing, releases, QA, troubleshooting, and client deployments. Collaborate with cross-functional stakeholders while applying modern cloud, API, microservices, data analytics, and AI technologies.

Designs and governs enterprise technology data architecture, including taxonomies, metadata standards, canonical data models, system-of-record strategies, lineage, and data quality frameworks. The role enables trusted data products, reporting, analytics, regulatory compliance, and executive decision-making across infrastructure, cybersecurity, cloud, AI, and technology management domains. It partners with architecture, engineering, risk, finance, governance, and data teams to establish scalable standards and drive adoption across a complex regulated organization.

Lead design, implementation, and operation of a Databricks-based enterprise technology reference data platform. Oversee data ingestion, integration, transformation, pipelines, security, observability, and platform reliability. Drive standards, enable data products and reporting, partner with stakeholders, and build a high-performing data engineering and DataOps team to support analytics and AI use cases.

Design, deploy, and operate enterprise AI/ML solutions across AWS, including machine learning pipelines, MLOps, Generative AI, LLMs, retrieval systems, knowledge graphs, and real-time applications. The role requires production software engineering, data engineering, model monitoring, governance, security, and responsible AI expertise. The engineer will partner with stakeholders, lead technical design discussions, influence architecture, and mentor team members while supporting scalable, cloud-native AI services.

Design, deploy, and manage hybrid on‑premises and multi‑cloud (AWS/Azure) infrastructure. Administer Linux and Windows servers, implement IaC and automation (Ansible, CDK/CDKTF), ensure backup/DR, perform vulnerability remediation, monitoring, and troubleshooting, and coordinate releases and infrastructure improvements.

Develops analytics, automation, dashboards, and data visualization solutions for Wealth stakeholders. Translates business needs into technical specifications, applies AI and analytics tools, identifies trends, creates actionable insights, documents processes, and enables self-service reporting through training and repeatable decision-support solutions.

Develop, test, implement, document, and support data and AI products. Translate business requirements into technical solutions, contribute to designs, build reusable frameworks and automation, perform regression testing, resolve production issues through root-cause analysis, and improve delivery and deployment processes. The role requires experience with data engineering, ETL/ELT, cloud platforms, structured and unstructured data, AI concepts, GenAI, prompt engineering, RAG, Agile delivery, and JIRA.

Backend software development internship involving ownership of an end-to-end project, designing, building, testing, and releasing scalable financial platform software. The intern will collaborate cross-functionally, work with a mentor, maintain existing codebases, and use technologies including Python/Django, Go, PostgreSQL, Kafka, Redis, Memcached, AWS, and Kubernetes.

Designs and delivers cloud-based insurance solutions for enterprise clients. Responsibilities include gathering requirements, creating solution architectures, collaborating with product and delivery teams, selecting technology components, supporting implementations, defining roadmaps, and advising clients. The role emphasizes AWS or GCP, scalable and highly available applications, relational and NoSQL databases, APIs, microservices, identity integration, and insurance business processes.

Build and maintain Python-based, cloud-native data pipelines and file delivery systems on AWS. Design scalable delivery for CSV/Parquet/JSON via S3, SFTP, and data marketplaces. Implement data quality, monitoring, CI/CD, and migrate legacy feeds to cloud architecture. Contribute to web-based monitoring/configuration, documentation, reviews, and production support.

Build and maintain full-stack web applications using Vue.js/Nuxt 3, TypeScript, Node.js, and AWS. Implement SSR, reusable components, Node APIs and integrations with headless CMS and third-party platforms. Contribute to AI-enabled marketing workflows, performance, accessibility, SEO, testing, monitoring, and troubleshoot across browsers, APIs, CMS, and cloud infrastructure. Participate in code reviews, documentation, and cross-functional planning.

Lead architecture and implementation of a unified, cloud-native data feed platform. Design scalable ingestion, transformation, and delivery pipelines; establish DataOps, governance, monitoring, CI/CD, and performance best practices; mentor engineers and influence cross-team technical strategy.

Build and maintain scalable backend cloud services and infrastructure for Autodesk AEC data products. Responsibilities include hands-on Java development, distributed systems and REST API design, AWS cloud services, automated testing and deployments, performance optimization, security, documentation, production on-call support, and mentoring developers. The role requires strong expertise in microservices, serverless architecture, databases, CI/CD, infrastructure as code, and secure high-performance enterprise services.

Own Supabase and AWS joint co-marketing across gaming, enterprise, startup, and AI segments. Produce campaigns, case studies, enablement assets, partner documentation, and executive-event content; coordinate with AWS field and marketing teams; identify campaign audiences with RevOps; and represent Supabase independently in partner discussions.

Leads partner technical discovery, designs and implements payment API integrations, builds scripts and lightweight services, and manages deployments from sandbox to production. The role develops AI-assisted engineering assets, delivery playbooks, and automation while collaborating with Sales, Product, and Operations. It requires customer-facing technical experience, software or solutions engineering expertise, and familiarity with APIs, integrations, cloud platforms, payments, and AI developer tools.

Develop and maintain Java-based financial microservices supporting global partner payments. Build reliable REST and message-driven systems, write tests, review code, use AI development tools, and maintain AWS and Terraform infrastructure. Collaborate with product and engineering teams while applying system design, reliability, observability, CI/CD, and database best practices.

Designs, develops, tests, and maintains cloud-based data pipelines and warehouses for large-scale datasets. The role involves data ingestion using Python and SQL, GCP services, production migrations, infrastructure troubleshooting, and optimization. The engineer collaborates with stakeholders to understand project goals and applies AI/LLM tools thoughtfully within data engineering workflows. Responsibilities also include distributed data manipulation, technical guidance, and maintaining scalable, cost-efficient data architecture.