Top AWS Jobs in Toronto

Build and scale Supabase Storage across client libraries, CLI, CDN, storage servers, and deployment infrastructure. Responsibilities include improving upload and download performance, asset optimization, edge networking, caching, observability, reliability, APIs, developer tools, and the storage explorer. The role also involves PostgreSQL and distributed-systems performance tuning, infrastructure operations, escalated support resolution, and end-to-end project ownership in an asynchronous, remote, open-source environment.

Own the technical side of deal progression for airline deployments: qualify opportunities, run demos and POCs, author integration and deployment architectures (PSS, APIs, data feeds, DNS, identity, networking), respond to RFPs/security questionnaires, scope SOWs and NFRs, and build reusable demo/reference assets to drive adoption and expansion while liaising between sales, engineering, and customers.

Own and prioritize cloud software product backlogs, translating clinical workflows, customer needs, and product strategy into actionable requirements, user stories, and acceptance criteria. Partner with Engineering, Architecture, DevOps, QA, UX, Product, and Regulatory teams on technical solutions, dependencies, Agile delivery, release planning, traceability, and compliance. Support scalable cloud products involving microservices, APIs, databases, security, and distributed systems.

Own the full lifecycle of production classification and detection models, including transformer fine-tuning, entity detection, behavioral risk scoring, training, serving, versioning, evaluation, drift detection, and retraining. Build SageMaker-based ML systems and define output contracts supporting audit and policy enforcement. Lead the evaluation harness and mentor a co-op while operating as the company’s sole ML engineer.

Develops, deploys, and monitors production data and machine learning pipelines. Responsibilities include data preparation, exploratory analysis, predictive modeling, feature and algorithm selection, model deployment, infrastructure development, and monitoring model performance, data quality, drift, latency, and reliability. The role also requires communicating insights, collaborating cross-functionally, and translating business problems into scalable data and ML solutions.

Lead the design and delivery of enterprise Territory and Quota Management features, including permissions, audit history, approval workflows, and reusable platform capabilities. Make product and technical decisions informed by customer needs, write and review design documentation, guide technical direction, and remain hands-on in building production systems. Collaborate across frontend and backend technologies while shaping team practices, system quality, and future product areas.

Leads multiple engineering teams developing AI and machine learning solutions, including LLM and RAG architectures. Sets technical direction, oversees hiring and development, manages budgets and resources, establishes engineering standards, resolves complex issues, and aligns delivery with senior stakeholders. The role requires hands-on Java, Python, machine learning, NLP, cloud, containerization, and Kubernetes expertise.

Provides Tier 3 Linux systems support for clients, including troubleshooting, alerts, patching, health checks, deployments, infrastructure roadmaps, cloud management, networking, containers, Kubernetes, virtualization, backups, and disaster recovery. The role involves client communication, onboarding, ticket and time tracking, independent problem-solving, documentation, and occasional after-hours support in a fully remote environment.

Designs and delivers scalable integrations for Jobber’s application marketplace. The role collaborates with business development, engineering, product, design, and external partners to create API-based solutions using REST and GraphQL. Responsibilities include integration strategy, partner technical support, software architecture, coding, testing, code reviews, roadmap input, process improvement, mentorship, and communicating complex technical concepts to diverse stakeholders.

Design, develop, test, deploy, and support scalable cloud-native Workforce Management and Customer Experience applications. Build Java and Spring Boot backend services, React and TypeScript frontends, REST APIs, microservices, integrations, and PostgreSQL data models. Contribute to Node.js components, Kubernetes deployments, Jenkins CI/CD pipelines, observability, security, and production troubleshooting. Collaborate with product, UX, QA, DevOps, architecture, and engineering teams while improving application performance, resilience, and maintainability.

Lead architecture and full-stack development for EASE, including TypeScript and Vue applications, backend APIs, automated testing, deployments, and production support across AWS and air-gapped on-premises environments. Own complex features, gather stakeholder feedback, improve performance and scalability, enhance CI/CD, and mentor engineers. The role also involves prototyping generative AI capabilities, integrating simulations, working with geospatial data, and maintaining secure, reliable distributed systems.

Design and implement enterprise contact center transformations using Amazon Connect, generative AI (Bedrock/Claude), serverless backends, and full-stack React tooling. Build contact flows, AI agents, CDK infrastructure, observability, CI/CD and migration solutions; collaborate with customers, mentor engineers, and ensure production reliability, security, and accessibility.

Leads the Core Systems engineering team responsible for reliable, scalable foundational platforms. Manages and develops engineers, guides architecture and technical tradeoffs, delivers incremental platform improvements, and strengthens operational practices through observability, incident reviews, and capacity planning. Partners with product engineering teams to build shared APIs, services, and tools while balancing reliability, security, scalability, maintainability, and technical debt.

Designs and delivers cloud-based insurance solutions for enterprise clients. The role gathers requirements, develops solution architectures, collaborates with product and delivery teams, supports implementations, evaluates technology components, and advises clients throughout deployment. Responsibilities emphasize AWS/GCP, scalable applications, relational and NoSQL databases, APIs, microservices, authentication, enterprise roadmaps, business architecture, and insurance processes across multiple lines of business.

Own the technical and automation engine for the go-to-market organization. Drive the GTM technology roadmap, automate workflows, translate business needs into technical requirements, oversee UAT, establish data governance and dashboards, and lead enablement and change management. Partner with Marketing, Sales Operations, Customer Adoption, and Data & Analytics to improve customer lifecycle processes and revenue execution.

Build and operate production software, cloud infrastructure, developer platforms, CI/CD pipelines, reusable tooling, and automated guardrails. The role spans AWS, Kubernetes, infrastructure as code, security, observability, reliability, and developer experience. It also evaluates AI-assisted development and agentic workflows while providing technical leadership across engineering, infrastructure, security, architecture, and product teams.

Leads a team of network reliability engineers responsible for production network services supporting a cloud platform. Manages hiring, coaching, priorities, on-call practices, incident response, customer escalations, and operational readiness. Applies SRE practices, observability, automation, error budgets, and post-incident improvement to increase availability and reduce operational toil. Partners with engineering, SRE, security, infrastructure, and support teams while guiding complex troubleshooting and risk-based operational decisions.

Design and develop advanced machine learning and generative AI solutions, including LLM fine-tuning, RAG architectures, prompt engineering, model evaluation, and MLOps. Architect scalable training, deployment, and retraining workflows on AWS using SageMaker and related services. Collaborate with engineering, QA, project management, and other stakeholders to deliver reliable AI applications and solve complex business problems.

Design, implement, monitor, and enhance network security and DLP controls across enterprise networks, endpoints, email, cloud, and web environments. Investigate security events, incidents, vulnerabilities, data leakage, and policy violations; perform root-cause analysis; coordinate remediation; and advise clients on network resilience, data protection, and practical security improvements. Collaborate with infrastructure, cloud, IAM, risk, compliance, privacy, and business teams in complex financial services environments.

Lead technical strategy and adoption of Databricks solutions for large financial services and insurance accounts. Partner with enterprise sales teams, executives, influencers, and technical resources to drive data and AI transformation, build technical champions, guide evaluations, and align solutions with business outcomes. The role requires expertise in big data, data science, cloud platforms, machine learning, programming, value selling, and technical leadership across global enterprise accounts.

Designs scalable, secure, and business-aligned technology solutions across customer applications, enterprise platforms, integrations, cloud, data, and digital transformation initiatives. Translates business needs into architecture blueprints, integration strategies, technical roadmaps, and governance standards. Partners with executives, product teams, developers, vendors, security, and data teams to modernize systems, manage risks, ensure regulatory compliance, and deliver resilient solutions.

Design, build, maintain, and scale full-stack software systems. Own technical areas across the product lifecycle, resolve complex issues, improve code and infrastructure quality, participate in reviews, document technical designs, and collaborate with engineering and product teams to deliver resilient solutions.

Own the company’s platform end to end across full-stack product development, Kafka and ClickHouse data/ML pipelines, cloud infrastructure, Kubernetes, Terraform, CI/CD, observability, security, and incident response. Build React and Node.js features, operate production systems, replace vendor-dependent infrastructure, and establish AI-assisted engineering workflows using tools such as Claude Code and Cursor. This is a hands-on technical leadership role for a senior individual contributor in a lean startup.

Own multi-cloud AWS and GCP infrastructure, Terraform automation, observability, CI/CD governance, security, secret management, and SOC 2 compliance automation. The role manages Kubernetes environments, logging and tracing pipelines, infrastructure migration, cost optimization, access controls, evidence collection, and audit-ready systems. It requires hands-on DevOps or SRE expertise, strong AWS and GCP knowledge, Terraform and GitHub Actions proficiency, and experience with modern data infrastructure and compliance frameworks.

Designs, deploys, and maintains production machine learning systems for identity resolution, scoring, deliverability, and personalization. Builds batch and real-time feature pipelines, develops classification models, integrates ML with graph databases, and manages monitoring, drift detection, retraining, and performance reporting. Partners with engineering to deliver low-latency APIs and scalable services while contributing to GPU-accelerated processing, MLOps standards, and large-scale graph computation.