Top AWS Jobs in Toronto

Administer commercial and technology contracts, including MSAs, SOWs, NDAs, DPAs, and amendments. Manage intake, drafting, review, routing, signatures, records, obligations, and key dates. Support privacy and compliance questionnaires, use AI tools for contract workflows, coordinate priorities across Sales, Finance, and Delivery, track turnaround targets, and recommend process improvements.

Lead hands-on architecture and engineering for production-grade AI applications. Establish development, deployment, security, testing, observability, validation, and incident-response standards. Productize scientist-built prototypes using cloud-native full-stack systems, agentic development tools, CI/CD, infrastructure as code, and reusable platform integrations. Partner with Quality, Cyber, platform teams, and R&D scientists to ensure regulated-system compliance, production readiness, and reliable operation.

Provides technical support for Cohesity data protection platforms across cloud and on-premise environments. Responsibilities include cluster deployment, maintenance, monitoring, performance tuning, troubleshooting Linux and storage issues, analyzing diagnostics, writing automation scripts, supporting APIs and PowerShell cmdlets, and communicating product improvements to engineering teams. The role requires expertise in Linux, networking, virtualization, storage, data protection, debugging tools, and cloud platforms.

Build and operate scalable backend services, APIs, and intelligent workflow capabilities for eBay’s AI platform. Responsibilities include architecture, system design, end-to-end feature delivery, performance optimization, observability, production troubleshooting, cross-functional collaboration, and mentoring junior engineers.

Lead high-impact AI solutions, overseeing architecture and deployment. Partner with stakeholders, coach engineers, and drive project success from inception to launch.

Own the customer side of a new GPU and CPU compute product as an internal startup. Responsibilities include product positioning, roadmap, developer adoption, self-service signup, go-to-market, pricing direction, messaging, website ownership, and collaboration with engineering on launches and success metrics.

Leads complex cybersecurity assessments, transformation programs, and technology implementations from mobilization through operational transition. Manages integrated workstreams, budgets, risks, dependencies, executive reporting, governance, and client relationships. Coordinates multidisciplinary teams and translates cybersecurity and regulatory requirements into remediation plans, roadmaps, control designs, and measurable outcomes. The role also oversees deliverables, steering committees, stakeholder communications, engagement economics, team development, and follow-on advisory opportunities.

Develop and support cloud-native full-stack applications using Java, Spring Boot, React, TypeScript, and Node.js. Build REST APIs, microservices, PostgreSQL data models, integrations, CI/CD pipelines, and containerized deployments. Implement observability, security, testing, and performance improvements while troubleshooting production issues. Collaborate with product, UX, QA, DevOps, architecture, and clients throughout the software development lifecycle.

Build backend systems, APIs, integrations, data pipelines, and workflow automations for customer procurement, ERP, finance, and operational workflows. Work directly with customers to clarify requirements, design scalable solutions, debug distributed integrations, and support technical deployments. Partner with Product and Engineering to identify reusable platform patterns while balancing customer-specific needs with long-term product direction.

Build backend services, APIs, data pipelines, integrations, and workflow automations for enterprise customers. Translate complex procurement, ERP, finance, and operational workflows into scalable technical systems. Work directly with customers, clarify requirements, debug distributed integrations, and partner with Product and Engineering to develop reusable platform capabilities. The role requires strong systems thinking, customer communication, and backend engineering expertise.

Designs and operates cloud infrastructure for large-scale ML training and production model serving. Responsibilities include distributed PyTorch training, GPU/TPU clusters, data pipelines for video and sensor data, infrastructure-as-code, CI/CD, observability, security, reliability, and developer tooling. The role partners across research and engineering, supports live customer-facing workloads, and mentors growing infrastructure teams.

Designs, builds, and maintains secure, scalable AWS cloud infrastructure for a SaaS platform. Develops Terraform-based Infrastructure as Code, automation, reusable platform services, GitHub Actions workflows, and CI/CD pipelines. Improves reliability, observability, disaster recovery, security, compliance, and cost efficiency across multi-account AWS environments. Collaborates with product engineering, SRE, security, and cloud operations teams while applying software engineering practices to infrastructure development.

Generate qualified sales meetings and pipeline through outbound email, calling, LinkedIn, and multichannel campaigns. Research accounts, identify technical decision-makers, manage prospecting campaigns, and coordinate with Account Executives on territory planning and lead quality. Refine messaging and outreach strategies, communicate value propositions to technical buyers, and maintain current product knowledge. The role is fully remote within specified U.S. and Canadian time zones, with some travel potentially required.

Build and operate secure, scalable cloud platforms and infrastructure. Responsibilities include infrastructure automation, Infrastructure as Code, Docker and Kubernetes environments, CI/CD pipelines, application deployment, monitoring, observability, troubleshooting, documentation, and cloud security. The role partners with engineering, infrastructure, security, and business teams to improve developer experience, reliability, scalability, and continuous delivery through reusable automation and self-service platform capabilities.

Lead end-to-end software architecture and hands-on engineering for enterprise data catalog services. Design scalable cloud platforms, knowledge graphs, relational data models, ingestion pipelines, APIs, and data lake layers. Establish resilient, secure, observable production solutions and advanced CI/CD practices. Champion AI-assisted development with governance and validation guardrails. Mentor engineers, guide architecture decisions, manage technical risk, improve operational quality, and support enterprise data discovery, governance, lineage, and self-service access.

Supports the configuration, development, testing, integration, troubleshooting, deployment readiness, and production support of Zafin SaaS solutions for financial institutions. Translates client requirements into technical specifications, data mappings, APIs, workflows, testing tasks, and documentation. Collaborates with business analysts, developers, QA, DevOps, architects, project managers, and clients while developing expertise in enterprise SaaS, banking technology, and technical consulting.

Leads enterprise pricing and business analytics strategy, building pricing and financial models, predictive analytics, dashboards, data governance, and AWS-enabled data workflows. Translates complex data into executive recommendations that improve profitability and commercial performance. Oversees the analytics roadmap, partners cross-functionally with Operations, Sales, Marketing, and Finance, and hires and develops a high-performing analytics team.

Leads the design, development, deployment, and production support of Python backend services and automation tooling. Builds REST APIs, administers Linux systems, writes Bash automation, manages systemd services, diagnoses production issues, and collaborates with DevOps on CI/CD, containers, and server hardening. Requires strong Oracle database, security, packaging, Git, and end-to-end service ownership experience.

Develop and maintain scalable backend applications using Java or Golang, REST APIs, microservices, Docker, Kubernetes, and cloud platforms. Responsibilities include deployment, CI/CD automation, testing, debugging, performance optimization, code reviews, architectural discussions, production troubleshooting, and collaboration with cross-functional teams. Experience with databases, Git, cloud-native systems, observability, messaging platforms, and infrastructure tools is valuable.

Lead and develop a team of data engineers building scalable real-time and batch pipelines and cloud data platforms. Set technical direction, manage major initiatives, and establish practices for architecture, testing, observability, reliability, and operational excellence. Partner with Product, Data Science, Analytics, and Engineering teams to deliver trusted data solutions supporting analytics, experimentation, machine learning, personalization, and high-volume marketplace experiences.

Owns the design and development of validation frameworks, automation infrastructure, conformance checks, and simulated network environments for NetBrain platform resources. Builds tooling to verify drivers, parsers, runbooks, intents, and integrations across vendors and platform versions. Analyzes coverage, resolves complex customer issues, tracks quality metrics, and improves resource reliability, scalability, and release readiness. Requires strong Python framework engineering, networking knowledge, API and data parsing experience, CI/CD expertise, and end-to-end project ownership.

Leads enterprise IT audit engagements, assessing technology risks, internal controls, governance, and regulatory compliance. Develops audit plans, oversees teams, advises senior stakeholders, evaluates emerging technology risks, uses analytics and AI to improve audit execution, and delivers objective reports to management and the Board. The role also manages resources, performance, audit quality, advisory engagements, and strategic initiatives.

Develop and productionize fraud detection machine learning models using large-scale behavioral, device, network, and transaction data. Lead investigations into complex fraud attacks, reconstruct attacker behavior, identify trends, and produce technical reports and customer-facing insights. Collaborate with product, engineering, operations, legal, executives, and customers to improve detection systems and automate analytic workflows.

Leads hands-on AWS cloud operations and platform engineering for mission-critical payment services. Responsibilities include Terraform automation, multi-account AWS governance, security and compliance automation, observability, resiliency, disaster recovery, incident response, operational readiness, cost optimization, and 24/7 production support. The role establishes cloud infrastructure standards and guardrails, drives reliability improvements, and influences architecture and engineering teams across the organization.

Leads architecture and technical direction for backend systems within a multi-tenant SaaS platform. Designs APIs and services, delivers end-to-end features, integrates data, machine learning, and AI capabilities, and improves performance, scalability, reliability, monitoring, and observability. Partners with Product, Design, and Data teams, leads design reviews, mentors engineers, and advances engineering standards.