Software Development Engineer, Measurement, Ad Tech, and Data Science

- 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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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, NY, New York - 184,900.00 - 250,200.00 USD annually
Help advertisers understand the true impact of their brand-building campaigns — delivering AI-driven measurement, performance reporting, and actionable insights that connect media investments with real customer outcomes across Amazon Ads. Your work will process billions of impressions and conversions daily, directly shaping how global advertisers optimize their brand spend.

As part of the Brand Measurement team, you'll define the technical strategy and delivery of solutions that empower advertisers to measure campaign effectiveness, identify optimization opportunities, and drive tangible business outcomes. You'll work backward from the customer to identify needs, build scalable event-driven architectures, and partner across engineering, data science, and design to ship robust, data-driven reporting products. If you're passionate about the intersection of generative AI and measurement at scale, this is your team.

Key job responsibilities
- Design and architect scalable, high-performance systems that leverage generative AI to deliver brand measurement insights at billions-of-events scale
- Develop and implement innovative machine learning algorithms to optimize advertising performance reporting and customer insights
- Define technical strategy and roadmap for AI-powered measurement solutions — working backward from advertiser needs to scalable architecture
- Collaborate with product managers, scientists, and design teams to create intelligent, data-driven advertising measurement experiences
- Lead technical design reviews and mentor engineering team members to raise the bar on quality and delivery
- Drive strategic technical decisions that shape the future of brand measurement platforms across Amazon Ads
- Build and operate event-driven architectures that process billions of impressions and conversions daily with high reliability

A day in the life
You'll spend your time designing and implementing sophisticated AI-driven systems that enhance how advertisers measure brand impact. You'll prototype innovative solutions with cross-functional partners, tackle complex technical challenges in measurement at scale, and drive adoption through close collaboration with internal and external stakeholders.