Top AWS Jobs in Toronto

Consultative Sales Engineer responsible for driving complex sales opportunities, designing cloud data security and data risk management solutions, delivering proof-of-value engagements and technical demonstrations, advising executive stakeholders, supporting partner channels, and coordinating cross-functional resources. The role requires cloud security, IAM, networking, databases, encryption, privacy, data governance, and strong technical communication skills.

Lead architecture and delivery of a composable, API-first Core Commerce Platform powering checkout, payments, OMS, inventory availability, loyalty, and post-order experiences. Drive integration of packaged solutions (SFCC, Fluent Commerce), payments, social and agentic commerce, and AI-native capabilities. Own SLAs, reliability, security (PCI-DSS), roadmap, and engineering standards while building and leading high-performing, on-site platform teams.

Leads engineers and technical leads in delivering AI-powered customer experience and contact center products. Responsibilities include solution architecture, technical design reviews, implementation planning, customer deployments, cross-functional coordination, risk management, operational readiness, and evaluation of emerging AI and CCaaS technologies. The role develops architecture diagrams, oversees complex software implementations, and guides integrations across cloud, AI, and contact center platforms.

Build and productionize AI agents for product analytics, integrating LLMs, tools, retrieval pipelines, and data systems. Develop data pipelines, evaluation frameworks, guardrails, telemetry, and monitoring. Diagnose agent quality issues, improve prompts and context, and contribute to proactive product intelligence systems. Collaborate with product and engineering teams to translate business needs into reliable agent designs while documenting work and following shared development standards.

Design, architect, and develop native Android features across the full SDLC. Own cross-functional, multi-platform system design, implement and test solutions, improve engineering practices, and mentor junior mobile engineers.

Manage, design, deploy, optimize, and scale persistent and transient AWS EMR clusters for batch data processing. Automate infrastructure with CloudFormation, Terraform, and CodePipeline; administer EC2, S3, and related AWS services; monitor pipelines; troubleshoot performance issues; and maintain security, patching, access controls, and cluster configurations. Preferred experience includes Hadoop, HDFS, AWS EKS, containerized workloads, and Kerberos.

Design and build Index Cloud, a globally distributed, multi-tenant compute platform across Kubernetes, bare-metal, and public cloud infrastructure. Own architectural decisions, infrastructure-as-code frameworks, platform APIs, SDKs, deployment systems, networking, storage, and distributed systems solutions. Drive technical strategy through RFCs and design reviews, improve developer productivity with self-service tooling, and mentor engineers across multiple teams.

Design and build Index Cloud, a globally distributed, multi-tenant platform operating across bare-metal and public cloud infrastructure. Responsibilities include architecting Kubernetes clusters, infrastructure-as-code frameworks, deployment systems, platform APIs, SDKs, and distributed systems. The role drives technical strategy through RFCs and design reviews, improves developer self-service, establishes security and tooling standards, mentors engineers, and collaborates across SRE, networking, security, operations, and software engineering teams.

Own complex, end-to-end full-stack features across Angular/TypeScript frontends, backend services, APIs, databases, and platform integrations. Lead architectural decisions, manage technical risks and dependencies, mentor engineers, coordinate delivery across teams, and improve testing, CI/CD, observability, and technical debt management. Serve as the squad’s technical anchor while partnering with Product, Design, QA, SRE, and platform engineering to deliver scalable customer-focused solutions.

Own and evolve cloud, on-premises, and edge infrastructure supporting AI, data, and product workloads. Design Kubernetes platforms, GPU scheduling, CI/CD pipelines, infrastructure-as-code, observability, security, and reliability practices. Lead infrastructure projects, incident response, platform strategy, and developer enablement while balancing cost, latency, reliability, and velocity. Mentor engineers and provide technical direction for scalable, production-grade ML and industrial systems.

Own SOC 2 Type 2 and ISO 27001 compliance programs while securing AWS, GCP, SaaS, infrastructure, identity, CI/CD, and software supply chains. Triage and remediate security findings, administer access and endpoints, support IT operations, manage auditors and customer reviews, debug cloud production issues, and build automated security guardrails, documentation, and postmortems.

Design, train, evaluate, and deploy production computer vision systems for industrial applications. Build detection, segmentation, classification, OCR, tracking, and visual-language pipelines; optimize real-time inference for edge and cloud environments; develop data and evaluation pipelines; fine-tune multimodal foundation models; and improve performance through quantization, pruning, and hardware acceleration. Collaborate across AI, engineering, product, and research teams on architecture, technical design, and production-grade AI systems.

Design and operate production backend services and AI infrastructure, including model serving, inference, data pipelines, vector stores, RAG systems, APIs, and microservices. Architect scalable real-time and batch systems, integrate and deploy LLM, computer vision, and machine learning models, and ensure reliability, observability, testing, and CI/CD. Collaborate with ML, product, and customer-facing teams while documenting systems and mentoring engineers.

Build and deploy production GenAI systems, agentic workflows, retrieval pipelines, and data services for enterprise customers. Learn operational domains firsthand, redesign business processes, create evaluation harnesses, write production Python or TypeScript, and deliver observable AWS-based systems. Partner with executives, engineers, and operators to drive adoption and measurable business outcomes while contributing reusable industry blueprints.

Lead the design and implementation of scalable Java microservices, data platforms, and batch and real-time pipelines. Optimize lakehouse technologies, event-driven architectures, cloud-native deployments, data quality, governance, observability, and performance. Establish schema contracts, testing, monitoring, SLAs, SLOs, and automated validation. Provide technical leadership, mentor engineers, collaborate with product, analytics, and AI teams, and drive modernization and engineering best practices as a hands-on contributor.

Lead PAM architecture and engineering for IDIRA/CyberArk Privileged Cloud, including custom CPM plugins, PSM connectors, MFA integrations, JIT access, cloud administration, and AI-agent credential vaulting. Establish onboarding standards, security controls, automation, auditability, and risk metrics across AWS, Azure, and GCP. Troubleshoot complex platform issues, remediate privileged-access risks, guide application teams, and support incident response involving compromised privileged accounts.

Leads consultative AI sales to enterprise accounts, from discovery and pursuit management through proposals, negotiation, contract signature, delivery partnership, renewals, and account expansion. Develops the client narrative, value case, pricing structure, and commercial strategy while collaborating with AI and consulting leaders on solution design. Targets executive buyers across retail, financial services, manufacturing, automotive, and healthcare, with performance measured by booked revenue, pipeline, win rate, engagement size, retention, and account growth.

Develop cloud-native Java applications, REST APIs, and high-throughput transactional services using Spring Boot and Kafka. Query data with SQL, monitor applications with Splunk and New Relic, and support CI/CD delivery. Collaborate in Agile teams to implement business-focused changes, troubleshoot systems, and contribute to product strategy. The role also involves using GenAI tools and may include microservices, Kubernetes, Docker, GCP, and AWS.

Lead the architecture and technical direction of Lyft’s mapping data platforms, including offline experimentation tooling, route simulation services, scalable pipelines, data governance, and observability. Own pipeline reliability and SLAs, evolve schemas, optimize SQL and data processing, build backend services and AI-assisted data tools, and mentor engineers. Collaborate with engineering, product, machine learning, and data science teams to improve routing quality and travel-time accuracy.

Own complex analytics engineering workstreams, design scalable analytical models and semantic layers, establish modeling and quality standards, improve AWS workload performance and reliability, and support AI-driven analytics capabilities. Partner with platform, product analytics, engineering, and governance teams; guide migrations and technical debt reduction; ensure privacy, security, and business fit; and mentor analytics engineers and analysts.

Owner of end-to-end production problems: design, build, experiment, ship, and measure outcomes across backend, frontend, data pipelines and AI. Act as a technical leader, reviewer, incident mitigator, and cross-functional partner to product and design while advancing AI-driven tooling and safeguards.

Own and set direction for a large domain, design cross-team architecture, build production systems (often AI-enabled), partner with product/design/data, coach senior engineers, and remain hands-on in code and delivery.

Build and operate secure, reliable backend platform services in Go or Rust. Responsibilities include event-driven workflows with Kafka and Temporal, identity and authorization, secrets and cloud KMS integrations, multi-tenant systems, GitOps deployments, secure third-party connectors, audit infrastructure, observability, performance improvements, failure recovery, and incident response.

Shape the architecture and evolution of Java-based SaaS platforms and shared backend services. Lead complex distributed-systems initiatives across multiple teams, remain hands-on with implementation and troubleshooting, and improve scalability, reliability, observability, security, and operational readiness. Establish engineering standards for Java development, APIs, testing, CI/CD, and production operations while mentoring senior and staff engineers and partnering with Product, Security, and Architecture leaders.

The Senior Platform Engineer will manage and build cloud-native infrastructures, develop backend features, ensure high availability, and interface with users while leveraging AI to enhance developer productivity.