Top AWS Jobs in Toronto

Lead development and maintenance of the core data platform: build performant pipelines, data warehousing, and ML infrastructure; partner with data scientists to produce production datasets; ensure data governance, quality, lineage, and accessibility; integrate cross-platform data sources; automate reporting and deliver stakeholder insights to enable data-driven decisions.

Founding full-stack engineer to build front-end and back-end features for month-end close automation, integrate with ERP/HRIS/CRM systems, design backend jobs and data ingestion, ensure code quality and CI/CD, implement LLM-driven workflows, and help grow the engineering team.

Develop and maintain backend Java applications and RESTful microservices across the full SDLC. Design APIs with Spring Boot, deploy to cloud/container platforms (AWS, Docker, OpenShift, Kubernetes), use CI/CD toolchains for build and quality, analyze complex system issues, implement security measures, and collaborate in Agile teams to deliver production-grade financial services systems.

Lead the creation of solution designs, ensure technical alignment across teams, improve IT processes, and provide technical leadership.

Lead and grow a distributed engineering team building Sangomas UCaaS platform. Drive architecture, scalability, reliability, CI/CD, observability, incident response, and cross-functional delivery for voice, messaging, provisioning, integrations and admin services.

Build and deploy production LLM/ML pipelines for patent workflows: retrieval, multi-step prompt pipelines, evals frameworks, fine-tuning, agentic workflows, monitoring, and cloud deployment. Collaborate with attorneys and cross-functional teams to convert domain expertise into robust, scalable inference and data solutions.

Lead the deployment of North in private cloud environments, collaborating with IT teams, designing strategies, and resolving technical issues.

Lead and grow a Data Engineering team to modernize enterprise data platforms (Snowflake/Databricks), deliver secure scalable batch and real-time pipelines, enable DataOps/MLOps, establish CI/CD and IaC practices, monitor platform health, and drive strategic platform migrations and performance optimizations with cross-functional stakeholders.

Operate and automate cloud-native infrastructure, maintain core platform services, perform system administration, implement IaC and configuration management, improve CI/CD and observability, collaborate across teams, contribute to incident response, and support security and compliance practices to improve platform reliability.

Design, build, validate, and maintain statistical and econometric marketing-mix and attribution models. Prepare and ETL structured/unstructured data, automate pipelines, run scenario simulations and experiments, and translate model outputs into actionable recommendations for clients via clear visualizations and presentations.

Lead design and delivery of complex full‑stack features, own architecture and AI development harness, mentor engineers, enforce code quality and standards, build integrations with EMRs and external data sources, and drive predictable, reliable product delivery.

Design, build, validate, and deploy econometric and marketing mix models to measure channel effectiveness and ROI. Prepare and automate ETL pipelines, run scenario simulations and incrementality tests, and translate analytical results into actionable client recommendations and visualizations.

The CPQ Lead Solution Engineer will drive engineering strategy and implementation of CPQ solutions, provide technical leadership, collaborate with teams, and ensure system stability.

Design, build, and deploy agentic AI workflows, LLM-enabled services, and cloud-native platform components. Integrate AI capabilities with enterprise systems, ensure production readiness, implement guardrails, testing, and monitoring, and collaborate with architects, delivery managers, and stakeholders to deliver secure, scalable AI-enabled automation and workflow solutions.

As a Senior Fullstack Engineer, you'll design and develop healthcare AI applications, architect scalable solutions, collaborate with teams, and optimize performance.

The Forward Deployed Engineer integrates Spellbook into legal workflows, managing enterprise deployments, building AI-native solutions, and enhancing user experience based on feedback.

As a Senior Solutions Engineer, you will engage in pre-sales conversations, design architecture, and deliver demos to help customers integrate LanceDB's AI solutions.

As a Senior Support Engineer, you will enhance customer support for LanceDB by building infrastructure, maintaining knowledge-bases, troubleshooting customer issues, and collaborating with engineering teams. Your expertise in distributed databases and proficiency in Rust and Python will help optimize cloud-native database deployments.

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

The Senior Site Reliability Engineer will lead service onboarding, maintain SLAs/SLOs, design secure infrastructure, automate operational tasks, and respond to incidents while ensuring system reliability and performance.

Develop and manage GoDaddy's eCommerce and SSO infrastructure, focusing on backend services and APIs using Java and Kubernetes on AWS.

Design and implement production GenAI solutions with a focus on RAG and Azure serverless platforms. Build backend APIs, scalable data pipelines for indexing/embedding/retrieval, deploy serverless Azure services, implement CI/CD and IaC, and enforce security, governance, and compliance while collaborating with cross-functional teams.

Senior QA Software Engineer responsible for testing and validating networking and cloud-native systems. Responsibilities include network protocol and security testing, cloud platform and container orchestration validation, triage and root-cause analysis of production issues, observability-driven debugging, and building/using automation and AI tools to resolve complex customer problems.

Lead client-facing integrations and implementations for an AI-native, compliance-focused travel platform. Design, build, and operate backend services, event pipelines, and data services on AWS. Ensure auditability, encryption/key management, consent and data lifecycle handling, and translate client feedback into product improvements while shaping architecture and early hiring.

Lead ownership, harden, and operate an AWS-native backend/platform: build APIs, event pipelines, data services, compliance features (audit logging, encryption, data lifecycle), deployment automation, testing/acceptance tooling, and shape architecture and engineering hiring.