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# Senior Software Engineer

- **Company:** Amazon.com, Inc.
- **Location:** Redmond, WA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Automation of Tests, C Sharp (Programming Language), C++ (Programming Language), Device Drivers, Python (Programming Language), Software Engineering, Systems Architecture, System Programming, TypeScript, Rust (Programming Language), Information Technology
- **Published:** September 19, 2026
- **Apply:** https://www.careerjet.com/job/usc7a7e78df92c91d49344a8577875fa12/eaa

## About the Role

Experience or demonstrated interest in operating system fundamentals is a plus; experience with existing AI inference toolchains is valued. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 5+ years of professional software engineering experience with coding in one or more languages such as C, C++, C#, Java, JavaScript, Python, Rust, or TypeScript, including designing automated tests and validation for the software you ship. Demonstrated knowledge of Server administration and management features. Familiarity with Server deployment and usage strategies in air-gapped or on-premises environments. Understanding of AI model catalogs, model servers, protocols and inference layers. Familiarity with the current state of the art around observability and diagnostics. Experience with systems software development, deep
systems architecture, driver development, and code architecture/design for complex software systems. Design and implement how we track usage, policy and efficiency for artificial intelligence capabilities. Build observability pipelines through telemetry insights, diagnostics, and health signals needed to measure how this on-prem infrastructure is performing. Define and develop the management layer for AI inference toolchains from model lifecycles and catalogs to language and protocol gateways. Design and implement validation plans to assess the quality of this infrastructure and evaluate the end to end workflows and life cycle experiences of such a solution. Coordinate with security and compliance teams to ensure this toolchain meets or exceeds platform release requirements.



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