Software Development Engineer II
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Description
Join Amazon’s Deployment Safety team and build the intelligent systems that keep our most critical cloud infrastructure running flawlessly. As a Software Development Engineer II, you’ll use AI and automation to design, test, and deploy updates for EC2 Frontier with precision and scale. You’ll own every stage of the development lifecycle—from crafting AI-enhanced deployment pipelines that predict risks to creating automated testing tools that catch defects before they reach production. By integrating machine learning models to analyze deployment data and real-time monitoring to flag anomalies, you’ll help millions of Amazon customers rely on infrastructure that’s safer, faster, and more resilient.
This role is for collaborative engineers who thrive on solving ambiguous problems, mentoring peers, and turning cutting-edge AI concepts into practical, high-impact solutions. If you’re passionate about blending cloud-native engineering with intelligent automation, we want to hear from you.
#AI #MachineLearning #DeploymentSafety #Cloud #Frontier
Key job responsibilities
- Design and implement software features across the full development lifecycle, including working backwards from customer needs, architecting solutions, writing production-ready code, testing, deploying, and operating services at scale.
- Identify root causes of operational issues and drive permanent fixes, while continuously improving system reliability, performance, and maintainability for your team's software.
- Mentor and coach other engineers through code reviews, design discussions, and knowledge sharing, helping raise the overall quality bar of the team's output.
- Evaluate technical tradeoffs between competing approaches, balancing short-term delivery needs with long-term architectural goals, and collaborate with stakeholders to ensure solutions align with business and customer priorities.
- Write clear documentation for the software you build — covering design decisions, operational runbooks, and system architecture — so that others can maintain and extend it effectively.
A day in the life
Your morning begins with a collaborative code review—leveraging AI-assisted tools to provide feedback that elevates the team’s code quality and readiness for deployment. After a focused standup where you align on AI-driven metrics and automation priorities, you dive into building a feature you scoped last week: writing clean, scalable code to integrate a machine learning model that predicts deployment risks. You pair with a teammate to tackle a tricky integration point, using real-time debugging tools to ensure seamless automation.
Post-lunch, you join a design review where you help streamline an architecture proposal—applying AI-first principles to simplify complexity and boost efficiency. Then, you investigate an operational metric that’s flagged by your anomaly detection system, tracing it to a root cause using ML-powered correlation engines. Within hours, you’ve drafted a fix that not only resolves the issue but also enhances your predictive safety models.
Your day balances deep, heads-down coding on cloud-native features with cross-functional problem-solving—all while driving operational excellence and mentoring peers. Every task you tackle reinforces our mission: building smarter, safer systems that millions of Amazon customers rely on daily.
About the team
Our team builds software that millions of Amazon customers and internal partners depend on daily. We combine operational excellence with AI-driven insights and automation-first practices to deliver reliable, high-quality systems. Every engineer’s voice matters here—we thrive on clear thinking, open collaboration, and a shared commitment to learning from both successes and challenges. As we scale EC2 Frontier to serve even more users, we’re focused on elevating the customer experience and empowering our team with cutting-edge tools, from AI-enhanced deployment pipelines to real-time monitoring frameworks.
This role is for collaborative engineers who thrive on solving ambiguous problems, mentoring peers, and turning cutting-edge AI concepts into practical, high-impact solutions. If you’re passionate about blending cloud-native engineering with intelligent automation, we want to hear from you.
#AI #MachineLearning #DeploymentSafety #Cloud #Frontier
Key job responsibilities
- Design and implement software features across the full development lifecycle, including working backwards from customer needs, architecting solutions, writing production-ready code, testing, deploying, and operating services at scale.
- Identify root causes of operational issues and drive permanent fixes, while continuously improving system reliability, performance, and maintainability for your team's software.
- Mentor and coach other engineers through code reviews, design discussions, and knowledge sharing, helping raise the overall quality bar of the team's output.
- Evaluate technical tradeoffs between competing approaches, balancing short-term delivery needs with long-term architectural goals, and collaborate with stakeholders to ensure solutions align with business and customer priorities.
- Write clear documentation for the software you build — covering design decisions, operational runbooks, and system architecture — so that others can maintain and extend it effectively.
A day in the life
Your morning begins with a collaborative code review—leveraging AI-assisted tools to provide feedback that elevates the team’s code quality and readiness for deployment. After a focused standup where you align on AI-driven metrics and automation priorities, you dive into building a feature you scoped last week: writing clean, scalable code to integrate a machine learning model that predicts deployment risks. You pair with a teammate to tackle a tricky integration point, using real-time debugging tools to ensure seamless automation.
Post-lunch, you join a design review where you help streamline an architecture proposal—applying AI-first principles to simplify complexity and boost efficiency. Then, you investigate an operational metric that’s flagged by your anomaly detection system, tracing it to a root cause using ML-powered correlation engines. Within hours, you’ve drafted a fix that not only resolves the issue but also enhances your predictive safety models.
Your day balances deep, heads-down coding on cloud-native features with cross-functional problem-solving—all while driving operational excellence and mentoring peers. Every task you tackle reinforces our mission: building smarter, safer systems that millions of Amazon customers rely on daily.
About the team
Our team builds software that millions of Amazon customers and internal partners depend on daily. We combine operational excellence with AI-driven insights and automation-first practices to deliver reliable, high-quality systems. Every engineer’s voice matters here—we thrive on clear thinking, open collaboration, and a shared commitment to learning from both successes and challenges. As we scale EC2 Frontier to serve even more users, we’re focused on elevating the customer experience and empowering our team with cutting-edge tools, from AI-enhanced deployment pipelines to real-time monitoring frameworks.
