Join a groundbreaking team shaping the future of Amazon Alexa, Machine Learning, and Generative Artificial Intelligence. We are developing cutting-edge products and services that define the standard for Amazon customers.

This Principal Engineer role is within the Aurora organization (Alexa Understanding, Runtime, ORchestration, and Applied Sciences), the core AI runtime backbone and horizontal intelligence unit for Alexa. Aurora is a dynamic science and engineering group dedicated to advancing research and delivering robust, scalable runtime solutions. Our mission is to revolutionize conversational AI through three key pillars: architecting essential AI runtime systems, advancing scientific solutions that link core conversational abilities, and transforming the scalability of builder creation.

You will operate at the forefront of AI research and large-scale production systems. Your work will involve architecting and implementing Pragmatic AI capabilities—AI that is not only technically advanced but also reliably useful, trustworthy, and accessible for everyday customer use.

Key responsibilities include leading the organization's technical direction, making critical architectural and systems design decisions for peak performance, scalability, and resilience. You will drive innovation in architectures leveraging Generative AI models and implement scalable solutions for technical initiatives.

Architect and build expansive, distributed systems that integrate complex datasets and support diverse access patterns. Mentor and inspire a team of skilled engineers and scientists, fostering their technical and professional advancement. Collaborate across Amazon to align technical visions and priorities, influencing decisions at senior leadership levels.

Define best practices for system architecture and engineering processes, upholding high standards for software quality and operational excellence. Lead engineering efforts that directly enhance customer experiences and business outcomes through Alexa+ and GenAI-powered services.

We are seeking individuals with deep expertise in distributed systems, ML inference infrastructure, or large-scale AI platform engineering. Demonstrated ability to set technical direction in ambiguous, high-stakes problem spaces with significant customer and business impact is essential.

Experience in driving cross-functional alignment across science, engineering, and product organizations, particularly in environments where unified ownership accelerates delivery, is highly valued. A proven track record of delivering production AI systems that serve diverse, global customer populations and a passion for building genuinely useful and trustworthy AI for real people are key.

Basic qualifications include 12+ years of non-internship professional software development experience, with at least 8 years in leading the design or architecture of new and existing systems. Experience as a mentor, tech lead, or engineering team leader is required, alongside experience collaborating across multiple organizations and influencing key outcomes. Technical leadership for multiple concurrent projects, driving strategic technical decisions, is also necessary.