Principal Software Engineer, Audible AI Foundations

At Audible we believe stories have the power to transform lives. Its why we work with some of the worlds leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.

ABOUT THIS ROLE
This is a rare opportunity to shape the future of audio content discovery and understanding at a massive scale. As the PE for Audibles AI Foundations you will be at the forefront of designing next-generation infrastructure and capabilities that will directly impact the daily entertainment experience of millions of customers.
You will have the chance to work with AI technologies including large language models multi-modal representation learning and real-time personalization systems. By architecting the core AI services that power Audibles content discovery recommendation and conversational experiences your work will be at the heart of delivering innovative and engaging experiences to users. Beyond the technical challenges this role offers the unique ability to influence the strategic direction of Audibles AI initiatives collaborating closely with cross-functional teams and driving the evolution of the companys AI capabilities. If youre passionate about building robust scalable and innovative AI systems that can transform the way customers interact with digital content this is an unparalleled opportunity to make a lasting impact.

ABOUT THE TEAM

Our team is responsible for the foundational AI infrastructure and services that power Audibles key customer experiences including content discovery personalization and conversational AI. We oversee the development and operation of a diverse portfolio of systems that sit at the intersection of machine learning natural language processing and large-scale distributed architectures. The current state of our existing systems reflects both the progress weve made and the challenges we now face as we strive to deliver increasingly sophisticated AI capabilities to our customers. Our core offerings include:
Content AI Infrastructure:
Semantic search and content understanding systems that need evolution to better handle audio-centric content
Content processing pipelines for attribute extraction and organization from various sources including customer reviews and metadata
Machine learning serving infrastructure for recommendation and personalization models requiring optimization for real-time interactive AI experiences
AI Foundation Services:
Large language model integration services for conversational AI and content understanding
Content understanding pipelines for processing multi-modal data and creating rich content representations
Feature management infrastructure for machine learning model support

ABOUT YOU
Youre in your element when youre being challenged and youre always eager to share your ideas take on responsibility and keep developing at an exciting pace. We look for people who show initiative set their standards high and see every failure as an opportunity to learn. Youre looking for an environment where you can thrive and help your team reach their potential. With opportunities to challenge yourself and lead a talented team to success youll find what youre looking for at Audible.

As a Lead Software Development Engineer you will be responsible for:
oArchitecture & Design:
Designing the scalable low-latency architecture for integrating large language models (LLMs) into our conversational AI and content understanding systems. This includes optimizing for streaming responses efficient context management and robust prompt engineering frameworks.
Creating the next-generation content processing and representation learning pipelines that can seamlessly handle the multi-modal nature of Audibles catalog including text audio and associated metadata.
Defining the overarching integration patterns and service mesh architecture that will enable the smooth flow of data and features across our diverse AI-powered systems.
oInfrastructure Evolution:
Architecting the high-performance real-time feature computation infrastructure that will power our personalization and recommendation models ensuring sub-millisecond latency and consistent data freshness.
Designing the evaluation and quality assurance frameworks that will be used to assess the performance accuracy and reliability of our AI systems including mechanisms for model versioning A/B testing and continuous monitoring.
Establishing the technical governance structure and best practices that will guide the development and deployment of Audibles AI foundation services across the organization.
oTechnical Strategy:
Crafting the long-term technical roadmap for the evolution of Audibles AI platform aligning it with the companys strategic vision and customer experience goals.
Influencing and collaborating with cross-functional teams in Data Science Product and Engineering to ensure the seamless integration of AI capabilities into Audibles overall technology strategy.
Defining the architectural standards design patterns and implementation guidelines that will be used to maintain consistency and reliability across Audibles AI infrastructure.
oOperational Excellence
The Principal Engineer will be a key driver of operational excellence across Audibles AI foundation services establishing robust frameworks and best practices for system reliability performance and scalability. They will architect comprehensive monitoring and observability solutions to ensure early detection of potential issues implement sophisticated alerting mechanisms and design automated recovery processes.
The PE will be responsible for creating resilient systems that maintain high availability while managing complex dependencies across the AI infrastructure. This includes establishing SLAs defining performance metrics and building automated testing frameworks to validate system behavior under various conditions. They will need to implement efficient capacity planning strategies optimize resource utilization and ensure cost-effective scaling of AI services. Additionally the PE will establish incident management protocols lead post-mortem analyses and drive continuous improvement initiatives to enhance system reliability and operational efficiency. Their focus on operational excellence will be crucial in maintaining the high-performance reliable infrastructure necessary to serve millions of customers while enabling rapid innovation and deployment of new AI capabilities.


ABOUT AUDIBLE
Audible is the leading producer and provider of audio storytelling. We spark listeners imaginations offering immersive cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

For basic qualifications enter as freeform no *
Bachelors degree in Computer Science Electrical Engineering or a related STEM field
10 years in software engineering
Previous experience with on-device AI/ML optimization including model deployment quantization and performance tuning

Same for preferred
Distributed Systems Architecture: A deep understanding of distributed systems design patterns including scalable data storage efficient caching strategies and robust failure handling mechanisms. This expertise will be crucial in architecting the next-generation of Audibles content processing and ML serving infrastructureMachine Learning Infrastructure: Extensive experience in building and operating large-scale ML platforms with expertise in areas such as model versioning automated deployment feature management and real-time inference. This knowledge will be critical in evolving Audibles ML platform to support the growing demands of AI-powered content discovery and Language Processing: Solid grasp of NLP techniques and architectures particularly in the context of content understanding semantic search and multi-modal representation learning. The PE must be well-versed in the latest advancements in LLM integration prompt engineering and cross-modal alignment to drive Audibles content understanding -time Serving Systems: Proficiency in designing low-latency high-throughput serving systems capable of handling the stringent performance requirements of Audibles customer-facing AI features. This includes expertise in areas like load balancing caching and dynamic model Recommendation Systems: Deep understanding of content personalization and recommendation architectures with the ability to create innovative approaches to model content relationships capture user preferences and drive engaging content discovery experiences.


* Bachelors degree in Computer Science Electrical Engineering or a related STEM field
* 10 years in software engineering
* Previous experience with on-device AI/ML optimization including model deployment quantization and performance tuning

* Distributed Systems Architecture: A deep understanding of distributed systems design patterns including scalable data storage efficient caching strategies and robust failure handling mechanisms. This expertise will be crucial in architecting the next-generation of Audibles content processing and ML serving infrastructure
* Machine Learning Infrastructure: Extensive experience in building and operating large-scale ML platforms with expertise in areas such as model versioning automated deployment feature management and real-time inference. This knowledge will be critical in evolving Audibles ML platform to support the growing demands of AI-powered content discovery and personalization.
* Natural Language Processing: Solid grasp of NLP techniques and architectures particularly in the context of content understanding semantic search and multi-modal representation learning. The PE must be well-versed in the latest advancements in LLM integration prompt engineering and cross-modal alignment to drive Audibles content understanding capabilities.
* Real-time Serving Systems: Proficiency in designing low-latency high-throughput serving systems capable of handling the stringent performance requirements of Audibles customer-facing AI features. This includes expertise in areas like load balancing caching and dynamic model routing.
* Content Recommendation Systems: Deep understanding of content personalization and recommendation architectures with the ability to create innovative approaches to model content relationships capture user preferences and drive engaging content discovery experiences.

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