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# Software Engineer

- **Company:** Amazon.com, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $125,000.0 - $175,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Infrastructure, Data Integration, Python (Programming Language), Machine Learning, Software Engineering, Cloud Platform System, Real Time Systems, Backend, Information Technology, Data Pipelines
- **Published:** September 16, 2026
- **Apply:** https://www.careerjet.com/jobad/us3b87ea3b527422259f5744d192f3204c

## About the Role

* Bachelor's degree in Computer Science or a related STEM field
 * 0 to 2 years of software engineering experience with a back-end focus
 * Hands-on experience building or maintaining data pipelines or data infrastructure
 * Experience with platform systems or operations automation
 * Able to integrate existing ML models into production systems
 * Able to work on-site five days a week in New York

Nice to Haves

 * Strong internship experience (recent graduates are welcome to apply)
 * Familiarity with a major cloud platform such as AWS or GCP, Are you passionate about applying AI and compilation techniques to automate legal contract processing at AWS scale? The AWS Contract Onboarding team is looking for a Software Devel…
 + 4 days ago

## Description

You would be a versatile back-end-focused engineer maintaining and extending the real-time systems at the core of the platform: the pricing and bidding engines, data infrastructure, and the tooling that keeps production running. This is a build-and-maintain role on live systems, not greenfield research.
What you'll be doing

 * Maintaining and extending core platform systems: pricing, bidding, and the data infrastructure behind real-time trading
 * Building and managing data integration and mapping workflows that synchronize data across multiple sources
 * Developing smaller systems and tooling to resolve production issues
 * Building ML feature pipelines and integrating existing ML models into production
 * Contributing across operations automation, platform features, and data infrastructure on two-week sprints

Tech stack: Python, with a major cloud platform (AWS or GCP)


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