Job summary
The Big Picture:
Advertiser Growth Tech (AGT) is an engineering team with the mission to enhance the Amazon Ads advertiser experience by delivering personalized, relevant, and engaging content across marketing channels to accelerate advertisers' desired business outcomes at each lifecycle stage. In support of this mission, we enable nine distinct marketing channels including: ads.amazon.com (A20M), Amazon Ads Academy (AAA), Email, SC, VC, AAC, KDP Portal Experiences, SMS, and WeChat. These channels are supported by our marketing infrastructure services and internal communication tooling products including Optimo, which is a communication creation and management tool that enables Amazon Ads teams to communicate with advertisers WW across email and in-UI channels.
We are a collaborative, highly-motivated and tight-knit group within Amazon Advertising. We are entrepreneurial with a high degree of ownership and a commitment to experiment and innovate. We encourage diversity of opinion and welcome dissent with respect and thoughtful debate as we search for the best solutions - and we'd love to hear yours. This is an opportunity to think about big problems that impact millions of our Advertisers and solve them with our collective ingenuity, all while engaging various teams across our broader org.
We are working on zero-to-one initiatives for the Amazon Ads organization. As part of this dynamic team, you will collaborate cross-functionally with product managers, scientists, and other engineers to define requirements, architect solutions, and deliver high-quality, scalable code. You will work on Agentic AI initiatives, contributing to systems that power Amazon's rapidly growing advertising business. Working alongside experienced Senior SDEs, you'll have excellent opportunities to solve complex problems in advertising technology while growing your career.
Key job responsibilities
What you'll be doing:
Design, develop, and deploy production-grade engineering and machine learning systems that deliver measurable customer impact at scale. Write clean, efficient, and well-tested code while collaborating with cross-functional teams to deliver scalable systems. Build multi agent applications using Agentcore and Strands framework. Own end-to-end AI/ML pipelines including data processing, model training, optimization, and inference infrastructure. Lead technical design discussions, mentor engineers, and drive architectural decisions for AI/ML solutions. Continuously learn new AI/ML technologies and engineering best practices while demonstrating Amazon's Leadership Principles, particularly Ownership and Deliver Results, in daily work.
BASIC QUALIFICATIONS
- 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
- Experience programming with at least one software programming language
- Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
PREFERRED QUALIFICATIONS
- 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
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, WA, SEATTLE - 143,700.00 - 194,400.00 USD annually
