Software Development Engineer – AI-Driven Data Platforms

Amazon Web Services (AWS); Seattle (WA); On-site; USD 144,000 - 194,000; Full time

Job summary

Amazon Web Services, Inc. in Seattle seeks a Software Development Engineer to design and deliver scalable data ingestion and ML-powered solutions within a Scrum team. You will work on a data-focused product using distributed systems and AWS services.

The role emphasizes OO design, secure architectures, and collaboration with applied scientists and ML engineers to enable GTM and customer engagement at scale.

Qualifications

• 3+ years of non-internship professional software development experience
• 2+ years of design or architecture of new and existing systems
• 1+ years of software development engineer or related occupational experience
• 1+ years of Object Oriented Design experience
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field

Responsibilities

• Design, develop, and maintain scalable data ingestion solutions
• Build highly available, secure, distributed systems in microservices and serverless architectures
• Develop serverless applications using AWS services with infrastructure as code
• Apply Machine Learning to solve data problems at scale
• Work with AWS technologies such as Glue, EMR, S3, DynamoDB, Redshift, Lambda, SQS, SNS
• Contribute to planning, design, implementation, testing, and operations as part of a Scrum team

Skills

Software development

System design

OO design

Scrum / Agile

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field

Tools

AWS

SageMaker

Glue

EMR

S3

DynamoDB

Redshift

Lambda

Job description

Amazon Web Services, Inc. in Seattle seeks a Software Development Engineer to design and deliver scalable data ingestion and ML-powered solutions within a Scrum team. You will work on a data-focused product using distributed systems and AWS services.

The role emphasizes OO design, secure architectures, and collaboration with applied scientists and ML engineers to enable GTM and customer engagement at scale.