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The Alexa AI org is looking for a Principal Engineer to join Aurora (Alexa Understanding, Runtime, Orchestration, and Applied Sciences) — Alexa's AI runtime backbone and horizontal intelligence organization. Aurora is a science and engineering organization that advances research while delivering robust, scalable runtime solutions. We revolutionize conversational AI through three core pillars: architecting mission-critical AI runtime systems, advancing latest science solutions that connect key conversational capabilities, and transforming how builders create at scale.
This role sits at the intersection of latest AI research and large-scale production systems, where you will architect and deliver Pragmatic AI capabilities — AI that is not just technically impressive, but reliably useful, trustworthy, and accessible to real customers in their everyday lives.
What makes this role unique
You will be building AI experiences that work across the full spectrum of human interaction — multi-modal (speech, text, image, video), multi-lingual (global locales with distinct linguistic and cultural requirements), and multi-model (orchestrating and routing across frontier and specialized AI models to optimize for accuracy, latency, and cost). Your systems will serve customers across a diverse range of endpoints and form factors, from voice-first devices to screen-based and mobile experiences.
AURORA influences the full Alexa+ agent execution path — from reasoning to evaluation to runtime — enabling you to operate in a structure designed to simplify interactions between components and the people who build them, accelerate feature development, and raise the bar on both operations and innovation velocity.
Infrastructure & Systems Complexity
- Design and own the architecture for AI capability routing and orchestration at massive scale, including intelligent query classification, model selection, and fallback strategies across heterogeneous AI back-ends
- Drive latency optimization across globally distributed inference pipelines, including model serving infrastructure, caching strategies, and real-time performance monitoring to meet strict customer-facing SLAs
- Build evaluation and quality assurance infrastructure — including offline test sets, live traffic sampling, model and prompt release gating, and automated regression frameworks — to maintain high accuracy and reliability as models and locales evolve
- Architect systems that support rapid iteration and safe deployment of new AI capabilities across global regions, with robust rollback, experimentation, and observability tooling
- Lead the design of core AI runtime platforms that power conversational experiences end-to-end, including speech processing, intent orchestration, and unconstrained interaction models that move beyond rigid turn-taking structures
Technology Vision
- Define the long-term technical strategy for how Alexa+ delivers high-quality, low-latency AI experiences to a global customer base, including the evolution of model integration patterns as the AI landscape rapidly changes
- Shape AURORA’s platform vision to empower internal and external engineers and scientists worldwide with modular, reusable platforms that accelerate innovation — while delivering accurate, responsive, and reliable conversational experiences to millions of end-users through operational excellence at scale
- Establish engineering standards and best practices for responsible AI deployment — ensuring accuracy, safety, and fairness are first-class properties of every capability shipped
- Influence the broader Alexa AI platform roadmap by identifying capability gaps, proposing architectural investments, and partnering with applied science, product, and platform teams to close them
- Drive science-to-production integration for specialized conversational AI capabilities, including reasoning, classification, and language understanding models
What we're looking for
- Deep expertise in distributed systems, ML inference infrastructure, or large-scale AI platform engineering
- Demonstrated ability to define technical direction in ambiguous, high-stakes problem spaces with significant customer and business impact
- Experience driving cross-functional alignment across science, engineering, and product organizations — particularly in environments where unified ownership across research, runtime, and evaluation accelerates delivery
- A track record of delivering production AI systems that serve diverse, global customer populations
- Passion for building AI that is genuinely useful and trustworthy for real people
Key job responsibilities Key job responsibilities • Lead Alexa AI AIDo org's technical direction, making critical decisions on architecture, infrastructure, and systems design for optimal performance, scalability, resilience and access patterns. • Drive innovation in architectures with GenAI models • Design and implement scalable solutions to org's technical initiatives • Architect and build large-scale, distributed systems that integrate complex datasets and support different access patterns. • Mentor and inspire a team of skilled engineers and scientists, fostering technical and professional growth • Collaborate across Amazon to align technical vision and priorities, influencing decisions at senior levels. • Define best practices for system architecture and engineering processes, maintaining 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.
About the team The AIDo (AI Domains) org is part of Alexa AI VP and Devices and Services SVP organizations. Our vision is to build an ecosystem of AI systems and services that elevate the core LLM model performance across endpoints, modalities, and locales. We are the horizontal Science and Engineering team that empowers Domains and Horizontal CX owners with transformative solutions that enable rapid, efficient scaling. AIDo represents a sophisticated global organization that spans multiple international locations including the US (Boston, Seattle), Germany, Italy, and India. The team's core mission is to develop and maintain AI systems and services that enhance the performance of core LLM models across various endpoints, modalities, and locales.
Basic Qualifications
- 12+ years of non-internship professional software development experience
- 8+ 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
- Experience collaborating across multiple organizations and influencing key outcomes.
- Experience as a technical leader of multiple concurrent projects, driving strategic technical decisions.
Preferred Qualifications
- Experience designing, building & operating large scale, highly available, secure cloud infrastructure.
- Experience with AI software systems including Agents.
- 15+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- 10+ years of highly scalable systems experience
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