Highlights
We just shipped our first wave of capabilities and are now designing the next, much larger version: large-scale data pipelines, real-time streaming, applied ML and generative AI, and an intelligence layer that lets teams query insights in natural language. Over the coming months and years, we are investing in a unified data-collection-to-insights platform, richer customer-journey metrics across every AWS channel, behavioral segmentation powered by ML, and an agentic insights layer driven by generative AI.
Numbers & Facts
| Location | Seattle, WA |
| Industry | Retail |
| Company Size | 10,000 employees or more |
| Year Founded | 1994 |
| Website | http://Amazon.com/militaryroles |
Description
Do you want to shape how AWS understands and improves the experience of millions of customers? The AWS Experience Analytics team is building a unified analytics, experimentation, and user-insights platform that spans every channel customers use - web, mobile, CLI, SDK, docs, and conversational interfaces. We just shipped our first wave of capabilities and are now designing the next, much larger version: large-scale data pipelines, real-time streaming, applied ML and generative AI, and an intelligence layer that lets teams query insights in natural language. This is an early, formative stage where the architecture and engineering norms are being set, so you won"t inherit a finished system - you"ll help define it.
As a Software Development Engineer on this team, you will own features end to end - from shaping requirements with product and science partners to shipping production services that AWS service teams rely on to find and fix customer friction. If you"re excited about combining open-source technologies, AWS services like Redshift and Kinesis, and big-data and ML techniques to drive the future of the AWS customer experience, we"d love to hear from you.
Key job responsibilities
- Design, build, test, and operate scalable services and data pipelines that power the analytics platform, ensuring reliability and fresh data for downstream consumers.
- Own a meaningful component or feature area end to end - from system design through production deployment and ongoing operations - bringing clarity to problems and identifying simple, maintainable solutions.
- Collaborate with product managers, applied scientists, and partner engineering teams to translate requirements into working software that improves customer-journey and experience-health metrics.
- Contribute to code reviews and mentor teammates, raising the bar on code quality, documentation, and engineering standards across the team.
- Evaluate and integrate generative AI tools and techniques where they can accelerate development or improve the platform"s insights capabilities.
About the team
AWS Experience Analytics is a newly formed organization with a rapidly expanding charter. We own the services and data warehouses AWS uses to gather quantitative insights (analytics, experimentation) and qualitative insights (user feedback, ratings) and turn them into actions that improve the AWS customer experience. Our customers are the service teams across AWS who need reliable metrics and tooling to understand how people use their products.
Over the coming months and years, we are investing in a unified data-collection-to-insights platform, richer customer-journey metrics across every AWS channel, behavioral segmentation powered by ML, and an agentic insights layer driven by generative AI. It"s a collaborative, builder-friendly environment where engineers take on increasing scope as the platform grows.
About Company
At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.
Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.
It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here
Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.
It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here
Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles