Join Amazon's Everyday Essentials (EE) Science team as a Software Development Manager and lead the engineering efforts that bring advanced scientific insights into production. This role is pivotal in developing the intelligence behind customer discovery, reordering, and personalization of everyday products. You'll leverage cutting-edge technologies like Generative AI, large language models (LLMs), and machine learning to enhance recommendations, substitutions, subscriptions, and create next-generation AI-powered shopping experiences across Amazon.

This is an exciting opportunity to shape the future of shopping, making it more intelligent, personalized, and seamless for millions of customers worldwide.

As a Software Development Manager, you will lead and cultivate a high-performing software engineering team, focusing on individual growth plans and attracting top talent.

You will architect and own the technical strategy for production ML systems, encompassing real-time inference, batch ML pipelines, and underlying data infrastructure.

A key responsibility involves building and scaling production LLM systems, including comprehensive model management, fine-tuning, retrieval, evaluation, and observability.

Collaborate closely with applied scientists to transition models from prototype to production, establishing robust experimentation and feedback mechanisms.

Drive operational excellence for all production services, ensuring high availability, low latency, efficient cost management, and excellent on-call health.

Foster an inclusive and dynamic culture where diverse perspectives are valued, leading to sustainable work-life harmony.

To excel in this role, you need a Bachelor's degree or its foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.

Possess a minimum of 3 years in engineering team management, complemented by 7+ years of overall engineering experience.

Demonstrate 8+ years of experience leading the definition and development of multi-tier web services.

Exhibit a strong understanding of engineering practices across the full software development lifecycle, including coding standards, code reviews, source control, build processes, testing, certification, and livesite operations.

Proven experience partnering effectively with product or program management teams and designing/architecting new and existing systems for reliability and scaling.