Software Engineer, RDS Patch Orchestration at Scale

Amazon

Austin (TX)

On-site

USD 144,000 - 194,000

Full time

14 days+
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Benefits offered by this job

Health insurance
401(k) matching
Paid time off
Parental leave

Job summary

Amazon Web Services (AWS) is seeking a Software Development Engineer for the RDS Platform scheduling team. The role focuses on building and operating the end-to-end patching and maintenance platform for Amazon RDS, including OS patches and version deprecations across millions of customer resources worldwide.

You will work on high-impact, customer-facing challenges at massive scale, aiming for zero-apparent downtime during maintenance and exploring GenAI-driven policy setup and AI-powered

Qualifications

  • 3+ years of non-internship professional software development experience.
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
  • Experience programming with at least one software programming language.
  • Bachelor's degree in computer science or equivalent.

Responsibilities

  • Work on high-impact, customer-facing challenges at massive scale with a focus on zero-downtime maintenance for RDS and Aurora.
  • Develop AI-powered scheduling and GenAI-driven policy setup to improve patching efficiency and safety.
  • Collaborate with PEs and Sr. SDEs across RDS and Aurora to shape the future of how AWS databases handle maintenance.

Skills

Software development
System design
Programming languages

Education

Bachelor's degree in computer science or equivalent

Job description

Amazon Web Services (AWS) is seeking a Software Development Engineer for the RDS Platform scheduling team. The role focuses on building and operating the end-to-end patching and maintenance platform for Amazon RDS, including OS patches and version deprecations across millions of customer resources worldwide.

You will work on high-impact, customer-facing challenges at massive scale, aiming for zero-apparent downtime during maintenance and exploring GenAI-driven policy setup and AI-powered

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