Top AWS Jobs in Toronto

Design, deploy, and operate production-grade Generative AI agents and GenAI workflows for clinical trial optimization. Build scalable cloud infrastructure, automate via IaC and CI/CD, integrate LLM routing and monitoring (latency, token usage, hallucination detection), and collaborate with AI engineers and data scientists to move models from research to reliable production services.

Lead and mentor engineering teams to design, architect, and deliver scalable, maintainable software. Drive cross-team initiatives, partner with Product and Design, participate in code reviews, promote engineering best practices, and spend time on Staff Dev Projects to reduce technical debt and explore emerging technologies.

Lead analytics-driven client acquisition, lifecycle and campaign optimization for wealth management. Translate data and market insights into targeting, measurement, and AI-enabled recommendations. Build tracking frameworks, dashboards, and closed-loop learning to optimize leads, journeys, and channel performance. Partner cross-functionally to design and execute lead programs, run test-and-learn initiatives, and support stakeholder adoption of analytics and self-serve tools.

Lead architecture and implementation of CoCounsel's backend, AI orchestration, and identity systems. Define AI-native patterns, ensure scale, reliability, and security for production LLM/agent workflows, mentor engineers, and collaborate across product, ML, platform, and security teams to deliver auditable legal AI solutions.

Lead architecture and scaling of CI/CD infrastructure for Kubernetes/Docker microservices, drive continuous deployment strategy, integrate AI-powered developer tools, collaborate with partner teams, mentor engineers, and participate in on-call rotation to maintain platform reliability.

Work directly with strategic customers to design, build, deploy, and operate production AI and data systems on Shakudo. Responsibilities include discovery, architecture, data pipelines, RAG/agent workflows, Kubernetes/cloud deployments, production support, governance, and driving adoption and measurable business outcomes.

Design, implement, and optimize monitoring and alerting across cloud infrastructure. Manage Extreme Cloud products, troubleshoot infra and application issues, improve deployment automation for Kubernetes microservices, enhance availability and scalability, provide 24/7 support, and participate in cloud security and compliance across distributed teams.

Design, build, and maintain Spark-based data pipelines and platform services for sales compensation calculations. Improve data modeling, reliability, observability, testing, and scalability. Partner with Product, Engineering, and Analytics to translate business requirements into deterministic, production-grade data systems and participate in design and code reviews.

Design and build backend services for complex enterprise workflows, own data models and service reliability, improve scalability and observability, partner with Product, participate in design/code reviews, and mentor peers.

Work directly with enterprise customers to design, build, and deploy production voice AI applications. Integrate Retell APIs/SDKs, develop conversational workflows, debug telephony/SIP and infrastructure issues, optimize AI behavior and prompts, lead technical onboarding, and drive product improvements from proof-of-concept to production.

Design and execute manual and automated test plans for Android and iOS apps, APIs, and backend services. Build and maintain mobile automation frameworks, validate AI features, integrate tests into CI/CD, track defects, perform database validation, and collaborate with cross-functional teams to ensure product quality.

Lead the software engineering division focusing on infrastructure, resiliency, and compliance. Oversee the SDLC, mentor teams, manage cloud and hybrid environments, and ensure system stability and security within regulatory frameworks. Drive AI integration and foster a high-performing, inclusive team culture.

Ownership of QA for a SaaS product: design and run manual and automated tests, validate APIs, integrate tests into CI/CD, perform regression and performance testing, and research AI/LLM-driven test automation while working cross-functionally.

Join the Platform squad to build and maintain a Typescript-based serverless microservices platform on AWS. Improve cloud availability, security, CI/CD, public APIs, data pipelines, internal DevOps libraries, and developer tooling while collaborating across product and engineering teams.

Perform product-focused analyses and A/B tests to generate actionable insights; build dashboards and KPIs; ensure data quality; synthesize diverse data sources; present findings to stakeholders and senior leadership to guide product and business decisions.

Design, develop, and deploy AI-first software features within an agile Editorial Tools & Services team. Translate business requirements into technical designs, produce documentation, research new technologies, participate in releases and testing, collaborate with QA and operations to ensure stability and high availability, and validate AI-assisted code for correctness, security, and performance.

Build high-performance API services and production-grade Generative AI systems. Design and implement end-to-end RAG pipelines, vector stores, embeddings, and latency-optimized generators. Develop agentic AI using LangChain/CrewAI/Semantic Kernel, integrate LLM APIs and AWS Bedrock, manage CI/CD and ML pipelines, and apply evaluation frameworks to detect hallucinations and optimize performance.

Support internal IT audit activities including ITGC and application control testing, SOX compliance, remediation tracking, and data analytics to identify risks and anomalies across enterprise systems.

Design and maintain reusable Terraform modules and CI/CD frameworks (GitHub Actions) integrating security scanning (Snyk). Architect resilient, cost-effective AWS infrastructure, enable observability, define standards for developer self-service, mentor junior engineers, and collaborate with SRE, security, and application teams.

The Software Engineer will design, develop, and maintain backend services and APIs, focusing on scalability and performance while collaborating with cross-functional teams.

Lead platform strategy and delivery, drive cloud modernization (AWS) and AI adoption, ensure platform performance, security, and scalability, manage cross-functional stakeholder relationships and vendors, oversee solution architecture and API/microservices design, and lead and develop a team while managing project financials and delivery across multiple workstreams.

Seeking a Senior Data Engineer to develop and maintain data pipelines, collaborating with data science teams to deliver accurate data for business insights.

Lead the architectural strategy for scalable and secure technology solutions, oversee development of systems using Java, Spring Boot, Node.js, and React, and enforce coding and DevOps standards.

The Data Integration Engineer will develop and maintain data connections between client sources and Prophix, focusing on cloud integration and automation, and mentoring team members.

Own and maintain Kotlin-based backend services for Faire's Insider membership program. Collaborate with Data Science, Product, and Design to prototype and productionize ML-driven features, run experiments and analytics to measure performance, optimize service design and performance, reinforce membership benefits across customer surfaces, and mentor engineers on architecture and best practices.