Top AWS Jobs in Toronto

Designs, maintains, and automates resilient cloud infrastructure supporting Blue J’s generative AI platform. Responsibilities include infrastructure as code, Kubernetes and CI/CD management, monitoring, alerting, logging, data pipeline support, security and reliability improvements, incident prevention, cross-functional collaboration, and on-call participation.

Own end-to-end AI workflows, designing and operating agentic and LLM-based systems in production. Build reliable pipelines with structured outputs, validation, fallbacks, evaluations, observability, and audit trails. Integrate AI services with backend systems while managing cost, latency, data isolation, and regulated-finance requirements. Establish engineering patterns, review system designs, and mentor teams on effective use of coding agents and AI tools.

Designs, operates, and enhances enterprise cryptographic security platforms, including Venafi, ISG Crypto Vulnerability Scanner, and HashiCorp Vault. Builds automation and integrations, implements risk-driven controls, supports cloud and container security, and participates in incident response and 24/7 on-call rotations. The role leads security initiatives, audits, technology evaluations, project transitions, documentation, and collaboration with infrastructure, application, operations, vendors, and security teams.

Performs functional and automated testing for cloud-based applications in a quality assurance and release engineering team. Responsibilities include developing automation frameworks and scripts, creating test plans and cases, conducting QA tests, verifying outcomes, debugging automation environments, and supporting scalable cloud test infrastructure. The role is designed for graduates and candidates developing quality engineering skills.

Designs and operates scalable cloud infrastructure and CI/CD pipelines across AWS and Azure. Builds Infrastructure-as-Code with Terraform and CloudFormation, manages Docker and Kubernetes environments, and improves security, reliability, observability, disaster recovery, and deployment efficiency. Partners with engineering, architecture, product, and operations teams on cloud-native platforms, distributed systems, automation, incident response, and long-term platform strategy.

Build and ship full-stack AI product features using Python, Node.js, React, and TypeScript. Design APIs, integrations, data pipelines, and scalable architectures while supporting cloud infrastructure, CI/CD, security, observability, and reliability. Own projects from technical design through deployment and iteration, collaborate cross-functionally, lead code reviews, mentor developers, and improve engineering practices.

Own partner-sourced and self-generated enterprise sales motions for AI consulting services. Manage Anthropic and AWS relationships, qualify leads, run full sales cycles, prospect within Financial Services and Life Sciences, close consulting engagements, maintain joint pipelines, lead co-sell planning, support partner certifications and marketing, and collaborate with delivery teams on proposals. Build executive relationships and provide market intelligence to leadership.

Build and maintain scalable, reproducible pipelines and data infrastructure for large-scale bottom-up proteomics (DIA/DDA). Design quantification, normalization, statistics, and atlas data models. Provide scientist-facing QC tools and metadata/sample tracking, manage storage and deposition to public repositories, and co-author methods while enabling open, versioned releases and integrations with orthogonal datasets.

Build and deliver production backend, platform, and AI capabilities using C#/.NET and Python. Develop distributed systems, LLM applications, AI agents, retrieval workflows, MCP servers, document understanding, and scalable AI infrastructure. Provide hands-on Staff-level technical leadership through architecture, coding, technical direction, mentoring, deployment, reliability, safety controls, and production operations.

Own the technical direction, development, reliability, and migration of Faire’s data infrastructure. Build CDC and streaming ingestion pipelines from production databases through Kafka into Iceberg on S3, operate Airflow and Fivetran, and implement data contracts, quality checks, SLAs, and observability. Lead cross-team initiatives, mentor engineers, manage incidents and on-call responsibilities, and partner with data scientists, analysts, and engineering teams to deliver dependable analytical data platforms.

Design and build SWTCH’s automated end-to-end testing practice from the ground up. Develop functional, regression, integration, and E2E test suites for web, mobile, API, and backend products; integrate testing into CI/CD; investigate failures; track defects; and improve coverage. Partner with Product and Engineering to define testable requirements and edge cases, perform exploratory testing, and mentor engineers in automation practices.

Lead development and maintenance of high-performance financial systems, provide technical leadership across the software lifecycle, evaluate architecture and technology choices, and strengthen automation and secure development practices. The role includes designing scalable microservices and event-driven systems, mentoring engineers, reviewing code and designs, translating business requirements into technical plans, managing technical risks, and collaborating with product, QA, and business stakeholders.

Lead the development of reusable DevSecOps and cloud components, delivering automation, security controls, zero-touch deployments, telemetry, dashboards, and high-availability platform support. Partner with product and engineering teams to improve operational ownership, maintain secure configurations and baselines, modernize tooling, and support reliable production services. Mentor teams, deliver group OKRs, and communicate complex technical concepts clearly.

Leads infrastructure and platform demand planning across compute, cloud, containers, networking, databases, storage, security, observability and service operations. Coordinates dependencies, estimates, risks, governance, operational readiness, financial analysis and delivery commitments across engineering teams and service providers. Translates technical complexity into business recommendations while supporting secure, automated platform consumption and responsible AI adoption.

Train and operate machine learning models on Amazon SageMaker using AWS Trainium. Develop and optimize PyTorch training code for NeuronCore hardware, diagnose device and compiler issues, tune distributed workloads for throughput and cost, and deliver production training pipelines while collaborating directly with client and engineering teams.

Designs and leads secure AWS architectures for migrating critical banking systems from on-premises data centers. Responsibilities include legacy dependency mapping, migration strategy, landing zones, hybrid connectivity, infrastructure as code, security controls, regulatory compliance, disaster recovery, cost governance, audit evidence, and cloud modernization. The role partners with risk, compliance, security, architecture, application, and engineering teams while providing technical guidance and supporting regulatory examinations.

Lead cloud migration and platform engineering efforts, designing AWS architectures and migration plans from on-prem VMware to AWS. Perform migration assessments, tooling selection, wave planning, dependency analysis, security/compliance alignment, OS and database troubleshooting, and optimize post-migration performance while collaborating with stakeholders and platform teams.

Build AI-powered product features and scalable platform infrastructure for appointment-based businesses. Design, ship, and own production systems serving over 120,000 businesses and processing billions in payments. Use AI throughout the software development lifecycle, ensure reliability and performance at scale, and drive architectural improvements while collaborating with and supporting other engineers.

Build and scale frontend applications, backend services, APIs, integrations, and production systems. Own projects from technical design through rollout and maintenance, improve reliability, performance, scalability, and observability, and collaborate cross-functionally with Product and Design. Mentor engineers, contribute to architecture and engineering standards, resolve ambiguous technical problems, and use AI-assisted tools to accelerate development while maintaining sound engineering judgment.

Build and operate platform security services for Auth0 using Python, Node.js, or Golang. Design scalable security data pipelines, resilient microservices, cloud integrations, and platform security controls. Apply secure coding practices, manage service permissions, participate in technical design and code reviews, and maintain high engineering standards across AWS or Azure containerized environments.

Leads AI solution architecture across pre-sales, client engagements, and production delivery. Defines scalable reference architectures, evaluates models and frameworks, governs security, data residency, hosting, integrations, cost, latency, and reliability, and mentors AI and data engineers. Remains hands-on with code, prototypes, design reviews, and technical client presentations while shaping proposals and protecting engagement profitability.

Develop and administer Tableau Server, build optimized data sources and dashboards, write and tune SQL, and perform exploratory data analysis. Partner with business, product, and analytics teams to deliver scalable reporting solutions. Establish visualization standards, document analytical processes, and evaluate AI/NLP tools such as Amazon Q to improve self-service analytics and natural-language querying.

Lead architecture, development, modernization, security, and production operations for Okta’s large-scale Integration Network platform. Design APIs, data models, integration frameworks, and distributed systems while managing ambiguous, cross-team initiatives. Drive technical decisions, observability, vulnerability remediation, incident follow-up, and AI-assisted engineering practices. Mentor engineers and influence technical direction across product, architecture, and engineering teams.

Own product marketing for InfutorData, including market intelligence, positioning, pricing, messaging, sales enablement, thought leadership, content, and go-to-market strategies. Partner with Product Management, Sales, and Marketing on launches, releases, customer insights, and roadmap alignment. Measure marketing performance and create collateral, training, case studies, webinars, whitepapers, videos, and campaigns that strengthen differentiation, adoption, and revenue performance.

Build and deploy production-grade GenAI and Agentic AI solutions for enterprise clients. Responsibilities include designing LLM applications, RAG systems, AI agents, and multi-agent workflows; integrating APIs, databases, and business applications; deploying and scaling cloud solutions; optimizing reliability, security, performance, and cost; and partnering with technical and business stakeholders from initial problem definition through production deployment.