Top AWS Jobs in Toronto

Develop and architect backend-focused full-stack features for Words With Friends using C#, Ruby on Rails, Unity, cloud infrastructure, APIs, databases, and DevOps practices. Responsibilities include designing gameplay systems, optimizing performance, managing deployments and live operations, writing tests, reviewing code, collaborating cross-functionally, documenting solutions, contributing to architecture, improving development workflows, and mentoring junior engineers.

Lead measurement, monitoring, and diagnostic reporting for AI-powered personalization models. Build scalable data pipelines in GCP and BigQuery, develop automated alerts, support A/B testing, and create Tableau visualizations. Evaluate recommender systems and propensity models using statistical and predictive analytics, integrate insights into AI products, and communicate findings to technical and non-technical stakeholders while mentoring junior team members.

Lead full-stack software development across the software development lifecycle, owning technical design and fault-tolerant application architecture. Build user-facing and server-side systems using modern programming languages, databases, and cloud services. Establish engineering standards, improve developer tools and frameworks, contribute to high-level design, solve complex technical problems, and mentor junior and intermediate engineers.

Lead technical strategy for Cash App Banking’s server engineering team, drive architectural and infrastructure improvements, contribute hands-on code and designs, influence cross-functional technical decisions, and mentor engineers. Build robust, scalable banking systems using distributed services and modern cloud technologies while advancing AI adoption across the team.

Designs and supports AWS back-end services for Wizard of Oz Slots, develops PHP gameplay functionality, and maintains CI/CD pipelines and infrastructure-as-code tooling. Responsibilities include load testing, infrastructure optimization, monitoring, escalation support, code quality, process improvement, and mentoring engineers. The role requires experience operating high-traffic, low-latency systems, working with SQL and NoSQL databases, and collaborating in a distributed team.

Own and scale BuildOps’ customer-facing data platform, including CDC ingestion into Snowflake, dbt modeling, near-real-time pipelines, secure data sharing, platform observability, Terraform infrastructure, and warehouse optimization. Participate in on-call incident response, support internal teams, manage governance and access, and contribute through architecture decisions, documentation, code reviews, and mentorship.

Deploy, integrate, test, troubleshoot, and tune cloud, network, telecom, and software systems for customers. Automate integration and operational workflows using scripts, APIs, AI, and LLM-enabled applications. Prepare data, validate AI recommendations, monitor automation quality, resolve defects, document results, and follow security, privacy, safety, and responsible AI requirements while collaborating with technical stakeholders.

Designs scalable, secure software architectures aligned with business goals and architectural standards. Responsibilities include creating capability catalogs, leading Architectural Decision Records and high-level designs, participating in architecture governance, evaluating technologies, collaborating with stakeholders, mentoring engineering teams, and driving technology strategies. The role requires extensive software engineering and solution architecture experience, including public cloud expertise and work in regulated environments.

Designs and implements scalable, secure technology architectures aligned with business goals. Leads architectural decision records, high-level designs, capability catalogs, governance reviews, and technology strategy initiatives. Collaborates with business and technology stakeholders, evaluates emerging technologies, ensures compliance with architectural and security standards, and mentors software engineers and architects. Requires extensive software engineering and solution architecture experience, including public cloud expertise and work in regulated environments.

Engineer and operate enterprise security controls across on-premises, cloud, and isolated environments. Build security automation and infrastructure-as-code, partner with infrastructure and application teams on remediation and CIS/NIST compliance, support identity, vulnerability, logging, and cloud security tooling, and produce executive security posture reporting. The role requires Canadian residency or citizenship/permanent residency and Government of Canada Reliability Status screening.

Serve as the senior technical authority for security engineering in Canada's regulated environment. Engineer and operate security controls across on-premises, cloud, and isolated infrastructure; build automation and infrastructure-as-code; support identity, vulnerability, logging, and cloud security tooling; drive remediation against CIS and NIST baselines; and produce operational and executive security posture reporting.

Serve as the senior technical authority for security engineering in Canada’s regulated environment. Engineer and operate security controls across cloud, on-premises, and isolated infrastructure; build automation and infrastructure-as-code; support identity, vulnerability, logging, and cloud security tooling; drive remediation against CIS and NIST baselines; and produce security posture reporting. The role requires expertise in Linux, automation, DevOps, network security, system hardening, and at least two specialized security domains.

Own and advance MLOps practices for real-time machine learning systems, including model deployment, serving, scaling, monitoring, lifecycle automation, and infrastructure optimization. Partner with ML scientists, data engineers, and Product to operate reliable low-latency models in Databricks and AWS. Establish engineering standards, resolve production issues, review designs and code, mentor colleagues, and track model performance, reliability, and costs.

Own and advance MLOps practices for reliable, scalable, cost-efficient machine learning systems supporting ad selection. The role operationalizes models in Databricks and AWS, builds automated training and deployment pipelines, establishes model governance and monitoring standards, designs low-latency serving infrastructure, resolves production issues, maintains performance dashboards, reviews designs and code, and mentors colleagues.

Designs, builds, and operates shared machine learning infrastructure, including feature stores, model hosting, inference, training, evaluation, and rules engines. Leads large-scale distributed systems, reliability improvements, incident response, and safe deployments. Partners with applied ML teams to develop reusable platform capabilities, supports internal users, mentors engineers, and contributes to technical roadmaps and design reviews.

Develop and maintain Zynga’s full-stack advertising technology platform, including SDK and server components. Improve performance, scalability, reliability, and system measurability; integrate third-party mobile advertising networks; translate product requirements into technical solutions; support game teams in production and integrations; and collaborate on architecture, emerging technologies, automation, and technical debt reduction.

Build and deploy AI agents that redesign and automate business workflows across Justworks International. Identify high-impact opportunities, map processes, define human-in-the-loop systems, integrate business platforms, and ship production agents. Own evaluation, monitoring, quality, cost, latency, adoption, and business KPIs while partnering with AI, operations, customer success, and leadership teams.

Leads multiple software engineering teams building scalable, resilient applications that reduce fraud and improve customer experience. Responsibilities include people leadership, talent and succession planning, engineering craftsmanship, application availability, resilience, scalability, hands-on development, technology experimentation, and mentoring. The role also influences product and business stakeholders on strategy and roadmaps.

Leads the technical direction and roadmap for MongoDB’s GTM analytics model portfolio. Designs statistical and machine learning models, builds SQL/Python data pipelines, develops governed BI assets, and measures business impact through experimentation and causal analysis. Partners with senior GTM stakeholders on forecasting, segmentation, territory design, account prioritization, and pipeline health. Delivers executive recommendations, establishes model governance standards, mentors analysts and data scientists, and drives adoption of analytics products across global sales operations.

Designs, builds, and maintains scalable enterprise backend applications and APIs using C#, .NET, AWS, and microservices. Responsibilities include applying software design best practices, developing highly available systems, supporting security and scalability, collaborating with product and engineering teams, improving processes, and evaluating AI-generated code for quality, security, performance, and maintainability.

Develop backend systems and continuous delivery platforms that improve developer productivity, automation, release safety, and software delivery speed. Collaborate with engineering teams and stakeholders, balance speed with reliability, write tested and extensible code, debug large codebases, participate in code reviews, and contribute to team growth.

Own and deliver backend infrastructure for machine learning model training and serving. Design and operate highly available distributed systems, lead technical initiatives, improve engineering standards, support on-call operations, collaborate cross-functionally, and mentor engineers. The role emphasizes reliable shared platforms, developer velocity, system scalability, and production-quality software.

Own and deliver quarterly engineering goals for an ML feature platform, lead solutions to ambiguous backend and distributed-systems problems, and collaborate with product, design, and analytics teams. Maintain platform reliability through metrics, availability monitoring, and on-call support. Establish code quality and design standards, address technical and business issues, contribute to scalable system design, and mentor engineers while building highly available backend systems.

Build and maintain scalable integration and end-to-end test automation frameworks and CI pipelines. Optimize test execution, improve stability and reporting, support engineering teams with triage and best practices, write technical specs/ADRs, participate in on-call rotation, and collaborate across regions to evolve the companys test strategy and developer productivity tooling.

Design, build, and operate shared backend platforms and frameworks for data acquisition, processing, and access. Lead projects from architecture through production, develop event-driven and batch or streaming systems, and improve reliability, observability, scalability, and data quality. Collaborate with software engineers, data engineers, and data scientists, make architectural trade-offs, mentor engineers, and contribute to technical standards. The role may also involve external data integrations and analytics and machine-learning data systems.