Top AWS Jobs in Toronto

Build and maintain front-end features for an AI-driven contract management SaaS. Collaborate with engineers, data scientists, product, and design; own functional areas from development to production; mentor teammates; apply modern dev practices to deliver scalable, user-centric solutions.

The Senior Manager, Business Operations will lead contract management, support financial operations, ensure compliance, and optimize internal processes while enhancing client relations and business strategy execution.

The Technical Architect develops scalable platforms and systems, collaborates with product teams, and leads architecture across data solutions and integrations, ensuring best practices and mentoring developers.

The Associate AI Engineer will assist in building AI-powered backend services, integrating APIs, and developing data pipelines while collaborating with experienced engineers and teams.

Lead and operationalize production across AWS and colocation systems. Unify SRE, DevOps, CloudOps, Security, and DBA teams to ensure reliability, performance, incident management, observability, compliance (PCI, SOC2), vendor management, and ITSM maturity. Drive cloud strategy, scalability, and operational excellence.

Lead backend and AI orchestration systems for CoCounsel Audit: design and operate scalable, low-latency AI workflows, integrate LLMs and retrieval systems, mentor engineers, set platform strategy, and ensure reliability, observability, and auditability at production scale.

Operate and automate cloud-native infrastructure across environments; maintain core platform services; troubleshoot and optimize workloads; implement IaC and configuration management; build automation to improve reliability; support CI/CD, observability, incident response, security, and compliance practices.

Lead design and implementation of Generative AI solutions for capital markets, building agentic frameworks, RAG, embeddings, and NLP models. Integrate tools into existing systems, guide teams, oversee experimentation, fine-tuning, deployment, and monitoring while researching advances in deep learning.

Build and lead a new Canada-based engineering team to deliver agentic AI features for the Viewer MCP. Hire ML/software engineers, define technical strategy and roadmap, ensure delivery quality (CI/CD, testing, observability), embed AI evaluation and responsible-AI practices, and partner across product, UX, and platform teams to productionize ML services.

Design and implement scalable, low-latency backend systems for Lyft Pricing. Lead multi-person projects, write maintainable and tested code, mentor teammates, participate in incident response, and collaborate with Product and Science on pricing solutions.

Lead full software development lifecycle: translate requirements to designs, write and test Java/Spring Boot microservices, integrate systems and APIs, deploy cloud-native AWS/serverless applications, ensure security, performance and reliability, and mentor/manage development activities and SDLC processes.

Design, build, and scale backend services and asynchronous distributed pipelines for document processing and workflow automation. Own infrastructure on AWS (including queueing systems like SQS), improve reliability, performance, and observability, integrate OCR/AI where appropriate, collaborate with product and customer teams, mentor engineers, and contribute to architecture and production APIs.

Lead cloud cost-optimization for an AI product: analyze and reduce LLM and infra spend, build cost tracking/forecasting tooling, advise on elasticity/caching, establish cost SLOs and alerts, and drive cross-team cost-reduction initiatives.

Lead enterprise architecture and solution strategy for tokenization and digital asset platforms. Define end-to-end architectures, governance, smart contract standards, custody and KMS integrations, Web3 frontends/backends, regulatory compliance, and security auditing. Mentor teams, author architectural records, and drive delivery alignment from design through production.

Lead an omni-channel communications platform team to gather stakeholder requirements, prioritize a technical product backlog, define user stories, run agile ceremonies, track KPIs, monitor system performance, and drive roadmap and platform strategy to improve customer communication experiences.

Design, implement, operate and support on-prem and cloud-based RPA and agentic AI automation platforms. Lead production support, perform code reviews, translate business requirements into designs and code, manage integrations, enforce security and SDLC standards, and evangelize operational best practices across the organization.

Design, build, and maintain internal automation tools and integrations to automate employee lifecycle, identity and access management, and enterprise application workflows. Troubleshoot systems, support deployments and monitoring, write clean code, and maintain documentation, runbooks, and architecture diagrams.

Manage and grow a small ML/GenAI engineering team while remaining hands-on: design and implement GenAI systems (agents, RAG, tool use), build NLP solutions (NER, classification, retrieval, summarization), partner with PMs and engineers to scope and ship features, and coach engineers on technical and career growth.

As a Senior Platform Engineer, you will enhance the developer experience by building AI platforms, managing infrastructure, and collaborating across teams to improve software delivery.

Lead enablement of Canada P&BB data, analytics, and AI capabilities. Partner with product owners and business teams to define, prioritize, and deliver production data and AI use cases. Translate business problems into implementation-ready solutions, guide platform and cloud (AWS/Azure) implementations, align initiatives to target architecture and roadmaps, and collaborate across business, data, and engineering teams to ensure scalable, auditable production outcomes.

Own and grow a portfolio of East Coast enterprise clients: manage engagement health, drive renewals and expansions, run executive reviews, identify upsell/cross-sell opportunities, coordinate with delivery and BDM, and hit quarterly revenue targets while supporting AI/cloud adoption.

Design and build an internal platform and developer tooling to enable reliable, self-service deployments. Own a TypeScript-based Pulumi codebase and Kubernetes runtimes, implement IaC and GitOps patterns, define SLIs/SLOs and monitoring, and participate in production operations, on-call rotations, and incident response to ensure platform reliability and security.

The Manager of Data Operations will lead a team to ensure the reliability and scalability of data platforms, enforce operational standards, and implement CI/CD practices. Responsibilities include monitoring data quality, incident management, and collaborating with various teams to enhance data operations.

Develop and manage backend services using Python and Java, design databases, automate tasks, and mentor junior developers. Collaborate on architectural decisions and debug production issues.

Lead the design of generative AI solutions and multi-cloud architectures, translating business use-cases into scalable systems for enterprise deployments.