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Applied Scientist, AWS Agentic AI

Job in Santa Clara, Santa Clara County, California, 95053, USA
Listing for: Amazon Web Services (AWS)
Full Time position
Listed on 2026-11-04
Job specializations:
  • Software Development
    Software Engineer, AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 172000 - 222000 USD Yearly USD 172000.00 222000.00 YEAR
Job Description & How to Apply Below

Description Great code assistants have to understand code the way an experienced engineer does, not as a wall of text but as a living structure of symbols, calls, types, and dependencies that span an entire repository. Most AI tools today flatten all of that into tokens and lose the structure that makes real software navigable. Amazon Web Services (AWS) is assembling an elite team of scientists and engineers to fix that, and we are hiring an Applied Scientist to build the intelligence layer that lets our AI development tools reason about code through its true structure.

You will help create generative AI technologies, including Kiro IDE and CLI, that are transforming how software gets built.

You will design how we turn the many signals around code, from static analysis and symbol graphs to build systems and language servers, into a single unified representation our models can reason over. This is a build-oriented research role where the questions are still open: how to fuse heterogeneous code signals, how to represent a whole repository so a model can find and use the right context, and how to ground an assistant’s reasoning in the structure of real software rather than text alone.

Your work will reach millions of developers, and you will own this direction end to end, from framing the approach to shipping it in a product engineers rely on every day.

Key job responsibilities
  • Design a unified representation of code that fuses static analysis, symbol and call graphs, type information, and build system context
  • Build the methods and models that consume that representation to power code navigation, retrieval, and reasoning at repository scale
  • Invent and implement state-of-the-art machine learning solutions that operate at unprecedented Amazon scale
  • Deploy products that directly impact the daily workflows of millions of developers worldwide
  • Publish and present your work at premier ML, NLP, and software engineering conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, ICSE, FSE)
  • Accelerate innovation by working directly with customers to rapidly transition research breakthroughs into production systems
About The Team

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and Amaze Con conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Hybrid Work

We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Basic Qualifications
  • 3 years of building models…
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