Software Development Engineer, Agent Platforms & Services
Amazon · New York, New York, USA ·
- Category
- Software engineering
Define how AI agents operate in one of the world's largest advertising ecosystems — building agent orchestration, reinforcement learning from expert feedback, trust and permission systems, and scalable inference infrastructure that powers intelligent advertising decisions across Amazon Ads. This is a greenfield opportunity to give every advertiser, regardless of size or sophistication, access to the caliber of strategic campaign management previously available only through dedicated agencies.
Our team is developing an agent platform that coordinates multiple specialized AI sub-agents to execute complex, multi-step advertising workflows. You'll work with Applied Scientists on learning systems, partner with product teams on advertiser experience, and build the identity and authorization frameworks that keep it all secure. This is a small, high-ownership team where you'll ship fast, think in systems, and shape how AI transforms advertising from the ground floor.
Key job responsibilities
- Develop orchestration systems that coordinate multiple specialized AI sub-agents to execute complex, multi-step advertising workflows
- 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
- Partner with Applied Scientists to integrate reinforcement learning from human expert feedback into production agent systems
- Design and operate end-to-end evaluation systems that measure recommendation quality, detect regressions, and enforce quality gates
- Collaborate with cross-functional teams (product, science, partner engineering) to define integration contracts and onboard new consumers to the platform
- 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.
Our team is developing an agent platform that coordinates multiple specialized AI sub-agents to execute complex, multi-step advertising workflows. You'll work with Applied Scientists on learning systems, partner with product teams on advertiser experience, and build the identity and authorization frameworks that keep it all secure. This is a small, high-ownership team where you'll ship fast, think in systems, and shape how AI transforms advertising from the ground floor.
Key job responsibilities
- Develop orchestration systems that coordinate multiple specialized AI sub-agents to execute complex, multi-step advertising workflows
- 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
- Partner with Applied Scientists to integrate reinforcement learning from human expert feedback into production agent systems
- Design and operate end-to-end evaluation systems that measure recommendation quality, detect regressions, and enforce quality gates
- Collaborate with cross-functional teams (product, science, partner engineering) to define integration contracts and onboard new consumers to the platform
- 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.