Software Development Engineer II, RDS Telemetry Platform

About the role

We are looking for a highly skilled, experienced, and motivated software engineer to help us in our endeavour to make AWS the best place to operate relational databases. The RDS Telemetry Platform team builds and operates the infrastructure for collecting, ingesting, and routing database telemetry across the RDS fleet, including a Data Lake for fleet-wide analysis. The team also develops automated engines that detect performance anomalies, diagnose root causes, and deliver tuning recommendations using both traditional and generative-AI techniques. This is a rare chance for you to be a part of a highly visible team working at the intersection of database performance and AI, helping customers manage their growing fleet of Aurora and RDS databases.

Key job responsibilities

• Develop a product that captures and stores telemetry from Aurora and RDS databases and surfaces them to our customers through multiple downstream products.
• Explore and build innovative solutions that leverage this telemetry to help customers troubleshoot and optimize database performance and detect security threats.
• This product operates on millions of instances, and helps our customers monitor and tune the performance and security of their databases through timely and relevant metrics, as well as recommendations.
• Solve the hardest engineering challenges in distributed systems at massive scale. Ensure your solutions are super solid, scalable, efficient, and highly fault tolerant.
• Be excited by the opportunity to learn about and help solve our customers' challenges. Be passionate about an idea and take it seriously, but also be open to debate and innovation.

About the team

AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empowers us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Basic Qualifications

• 3+ years of non-internship professional software development experience
• 2+ years of programming using a modern programming language such as Java, C++, or C#, including object-oriented design experience
• 1+ years of contributing to new and current systems architecture and design (architecture, design patterns, reliability and scaling) experience
• Bachelor's degree or equivalent
• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence

Preferred Qualifications

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
• Experience in debugging, profiling, and implementing software engineering best practices in large-scale systems