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Senior Software Development Engineer, SPB Advertiser Guidance

Job in New York, New York County, New York, 10261, USA
Listing for: Amazon
Full Time position
Listed on 2026-01-06
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Location: New York

Description

We are looking for a Senior Software Development Engineer who will own the infrastructure, platform, and production systems that underpin our agentic advertiser guidance framework. In this role, you will lead the design, build, and scaling of core services such as tool orchestration, agent execution engine, evaluation pipelines, model serving/tuning infrastructure, and monitoring systems. You will work closely with applied scientists and engineers to translate prototype agent capabilities into robust, scalable production systems.

You will need to rapidly learn and apply new techniques in agent deployment, model tuning, reinforcement learning infrastructure, multi-step reasoning orchestration, and system optimization. You will build APIs, pipelines, and frameworks that allow agents to reason, plan, and act reliably at scale, ensuring low latency, high throughput, resilience, fault tolerance, versioning, and safety guardrails. A critical aspect of this role is being customer-obsessed: you will work backwards from advertiser needs to ensure that infrastructure decisions enable real customer-facing experiences.

You will also partner with cross-functional teams—science, product, operations—to continuously iterate the agentic architecture, evaluation metrics, and tuning loops. This is a high-impact role where you balance deep technical craftsmanship with product sensibility, setting standards, influencing architecture, and owning end-to-end delivery of agentic capabilities.

Key job responsibilities
  • Lead engineering strategy and roadmap for Sponsored Products Agentic Advertiser Guidance
  • Design and implement scalable architecture to host agent orchestration, tool invocation, state management, and feedback loops.
  • Build scalable, reusable data and tool registry
  • Construct evaluation pipelines (offline and online) to assess agent reasoning quality, performance metrics, safety constraints, and KPI impact.
  • Integrate and manage tuning pipelines (e.g. hyperparameter tuning, RL fine-tuning, preference optimization), and provide abstraction layers for scientists to plug in models.
  • Implement observability, logging, metrics, alerting, tracing, and drift detection for agent behaviors and model performance.
  • Ensure resilience, fault isolation, auto-scaling, batching, caching, resource allocation, concurrency control, and SLA compliance.
  • Rapidly prototype and evaluate new system designs or algorithmic patterns (e.g. streaming inference, memory caching, chaining of reasoning modules, tool embeddings).
  • Collaborate in design reviews, code reviews, system design, and cross-team architecture alignment.
About the team

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across  and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.

We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.

The Advertiser Guidance team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon’s retail ecosystem.

Our vision is to build a highly personalized, context-aware agentic advertiser guidance system that leverages LLMs together with tools such as auction simulations, ML models, and…

Position Requirements
10+ Years work experience
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