About the job
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.
Responsibilities
You will be responsible for developing a product that captures and stores telemetry from Aurora and RDS databases and surfaces them to our customers through multiple downstream products.
You will also be responsible for exploring and building 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.
You will be responsible for all aspects of engineering, including development, testing and deployment of these services.
You need to be comfortable taking ownership of the operational excellence of your service.
Qualifications
Minimum
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
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