Development engineer Jobs in Toronto, ON

Amazon's CloudTune organization is seeking a Software Development Engineer to join the Scaling Planner team and contribute to our suite of products across Reactive and Proactive Scaling. Our systems automate capacity management for thousands of EC2-based Auto Scaling Groups across Amazon's Stores, Devices, and Other (SDO) organization.

Proactive Scaling is the forward-looking engine at the core of Scaling Planner - it ingests business forecasts, applies scaling formulas via the Capacity Calculator, and generates capacity recommendations before demand arrives. This is how Amazon prepares for its highest-stakes moments, including Prime Day, Black Friday, and other High Volume Events. Reactive Scaling is the backstop to unplanned changes in demand - when systems come under stress that scaling can help smooth, we step in and provide automated emergency relief by pulling from a centrally managed capacity pool when real-time metric thresholds are breached.

As a Software Development Engineer II, you will own the design, delivery, and operation of systems across this portfolio with a primary focus on Proactive Scaling. You will partner with scientists, capacity managers, and service owners to ensure Amazon's infrastructure is always right-sized at the right time - powering services behind Amazon.com, Alexa, Prime Video, and digital devices.

Key job responsibilities
- Own the design, implementation, and operation of Proactive Scaling services that generate capacity recommendations using business forecasts, scaling formulas, and the Capacity Calculator.
- Build and improve the automated pipeline that calculates, schedules, and applies capacity overrides for peak events and daily scaling across supported regions (IAD, PDX, DUB, FRA, ZAZ).
- Contribute to Reactive Scaling systems that monitor real-time metrics (CPU, throughput via CloudWatch and PMET) and automatically adjust capacity when thresholds are breached.
- Drive integration between Scaling Planner, the Capacity Calculator (formerly CloudSpin), Fleet Management Console, and CloudTune Capacity Service to deliver seamless, end-to-end capacity automation.
- Define and monitor risk factors, efficiency metrics, and guardrails that trigger iterative improvements with customers to close automation gaps.
- Lead technical design reviews, author design documents, and influence the architectural direction of Scaling Planner.
- Mentor junior engineers through code reviews, design guidance, and operational best practices.
- Maintain high operational standards, including on-call responsibilities, monitoring, alarming, and incident response for services you own.

About the team
Scaling Planner is CloudTune's capacity automation engine for Amazon's SDO organization. We ensure that thousands of EC2-based services have the right capacity at the right time - whether that means proactively scaling up for Prime Day or reactively absorbing an unexpected traffic surge. Our Proactive Scaling capability is what sets us apart: instead of reacting to traffic spikes, we predict them using advanced forecasting and automatically prepare infrastructure weeks in advance. Reactive Scaling complements this by providing an automated safety net when real-world conditions deviate from forecasts. We work closely with CloudTune Science, capacity management, and service owners across Amazon. We value ownership, operational excellence, and building systems that remove manual toil so Amazon's engineers can focus on their customers.

BASIC QUALIFICATIONS

- 3+ years of non-internship professional software development experience
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design

PREFERRED QUALIFICATIONS

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

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