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# Software Development Engineer, Support Agent Intelligence and Evaluation

- **Company:** Amazon.com, Inc.
- **Location:** New York, NY, United States
- **Salary:** $158,100.0 - $213,800.0
- **Contract:** Internship / Graduate position
- **Skills:** Java (Programming Language), Artificial Intelligence, Software Applications, C Sharp (Programming Language), C++ (Programming Language), Code Review, Computer Programming, Learning Management Systems, Software Design Patterns, Perl (Programming Language), Object-Oriented Software Development, Software Engineering, Alwayson, Reinforcement Learning, Multithreading, Reliability of Systems, Information Technology, Build Process, Software Coding, Software Version Control
- **Published:** August 22, 2026
- **Apply:** https://dejobs.org/x/x/08EB0A2185964FF491E22BA50AE177D2/job/

## About the Role

* 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
 * 1+ years of software development engineer or related occupational experience
 * 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
 * 1+ years of Object Oriented Design experience
 * Experience programming with at least one software programming language, * 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
 * Bachelor's degree in computer science or equivalent

## Description

We are building the next generation of AI-powered advertising intelligence at Amazon Ads. Our team is developing an agent platform that gives every advertiser - regardless of size or sophistication - access to the caliber of strategic campaign management previously available only through dedicated agencies. You will work on agent orchestration, reinforcement learning from expert feedback, trust and permission systems, and scalable inference infrastructure that powers intelligent advertising decisions across Amazon's ad products. This is a greenfield opportunity to define how AI agents operate in one of the world's largest advertising ecosystems., * Develop orchestration systems that coordinate multiple specialized AI sub-agents to execute complex, multi-step advertising workflows

 * Collaborate with cross-functional teams (product, science, partner engineering) to define integration contracts and onboard new consumers to the platform
 * Build identity, authorization, and permission frameworks that enforce scoped access for diverse caller types
 * Implement feedback signal pipelines that capture expert judgment and route it into model improvement loops
 * Design and operate end-to-end evaluation systems that measure recommendation quality, detect regressions, and enforce quality gates
 * Partner with Applied Scientists to integrate reinforcement learning from human expert feedback into production agent systems
 * Own system reliability, observability, and performance for always-on agent infrastructure serving thousands of concurrent advertiser accounts

A day in the life

You might start the morning reviewing eval results from a newly onboarded agent skill, diagnosing why routing accuracy dropped 2%. By mid-morning, you're pairing with an Applied Scientist to tune the feedback pipeline that captures expert signals. After lunch, you're designing the permission model for a new integration. You end the day shipping an observability improvement that surfaces latency bottlenecks across the orchestration chain. Every day is different, but the thread is the same: making AI agents smarter, safer, and more reliable at scale.

About the team

We're a small, high-ownership team within Amazon Ads building the platform that makes AI agents accessible across the advertising ecosystem. Our charter is greenfield: we're defining how agent intelligence gets exposed to other engineering teams. We work closely with Applied Scientists on learning systems, product teams on advertiser experience, and platform teams on shared infrastructure. The team values builders who ship fast, think in systems, and are comfortable operating in ambiguity. If you want to shape how AI transforms advertising from the ground floor, this is the team.


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