Software Development Engineer III, Catalog Diagnostics & Analytics

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CA, Sunnyvale - 193,300.00 - 261,500.00 USD annually
At Amazon Selection and Catalog Systems (ASCS), we're solving one of the hardest AI challenges in the world: establishing product identity and relationships at unprecedented scale — billions of products, petabytes of multi-modal data, millions of sellers, dozens of languages, and infinite product diversity. Using Generative AI, Visual Language Models (VLMs), and multi-modal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog.

The Catalog Diagnostics & Analytics (CDA) team is at the forefront of this work. We own one of Amazon's largest data lakes (hundreds of petabytes), process catalog data at 100K+ TPS through a cost-effective micro-batch streaming architecture, and serve 2,000+ internal customers who rely on our datasets for daily business decisions. We're now building the next frontier: a production-grade, agentic AI platform that automates catalog diagnostics — delivering full data provenance, change audit trails, and explainability into every catalog change at Amazon scale.

We are looking for a Senior Software Development Engineer who can operate at the intersection of ambitious technical scope, organizational leadership, and deep expertise in GenAI and Agentic systems. If you thrive in fast-paced environments and want to push boundaries at the frontier of AI and distributed systems, we'd love to hear from you.

Key job responsibilities
- **Lead technical architecture** for CDA's agentic diagnostics platform — designing systems at the intersection of GenAI, transactional engines operating at 100K+ TPS, and large-scale information retrieval

- **Set technical direction** for how we instrument, evaluate, and close the accuracy and reliability loop for production-grade agentic AI solutions — translating ambiguous business challenges into tractable engineering frameworks

- **Drive AI-native development practices** across the team: prompt engineering, LLM integration, agentic architectures, retrieval-augmented generation (RAG), and automated evaluation and feedback loop frameworks

- **Influence without authority** — collaborate with Applied Scientists, Data Engineers, and partner teams across Amazon to define standards and patterns that others adopt

- **Own end-to-end delivery** — from design through coding, testing, deployment, and operational excellence — with full accountability for production reliability and customer impact

- **Raise the technical bar** through rigorous design and code reviews, mentorship of engineers, and establishing standards for no-code testing, deployment lifecycle tooling, and automated skill creation

- **Partner with senior leadership** to shape the roadmap, identify strategic investments, and represent CDA's technical perspective in cross-organizational forums

About the team
The Catalog Diagnostics and Analytics (CDA) team owns one of the largest data lakes within Amazon Retail, managing hundreds of petabytes through processing pipelines that push the boundaries of Amazon's technology infrastructure. We maintain foundational catalog datasets relied upon by 2000+ internal customers for day-to-day business decisions.

Our team pioneers data management technologies and architecture patterns across the organization, setting standards for others to adopt. We operate daily and hourly batch datasets alongside services processing catalog data at 100K TPS through a cost-effective micro-batch streaming architecture.

CDA also owns Catalog Diagnostics services that provide insight into catalog changes, enabling Amazon stakeholders to quickly identify and resolve catalog issues. We are building an agentic solution to automate and simplify catalog diagnostics—delivering transparency through data provenance and change audit trails that explain what changed, when, by whom, and why.

We are tackling foundational challenges in making agentic solutions production-ready, including full-cycle feedback loops, agent accuracy and evaluation frameworks, automated skill creation, and no-code testing and deployment lifecycle tooling.