Senior Software Engineer - AI-Driven Personalization at Scale

Amazon; Illinois; On-site; USD 120,000 - 230,000; Full time

Job summary

Amazon Development Center (Tel Aviv) is seeking a Software Development Engineer to design and build AI-powered personalization features at Amazon scale. You will own end-to-end delivery from design to production, mentor juniors, and raise engineering standards across teams.

You will work with product and science to experiment, measure impact, and iterate on experiences such as personalized recommendations and explanations using LLMs.

Qualifications

• 5+ years of professional software development experience.
• Experience with Java, C++, or C# including object-oriented design.
• Experience with full software development life cycle, including coding standards, reviews, source control, build, testing, and operations.
• Experience contributing to architecture and design for scalable systems.

Responsibilities

• Design, build, test, and operate production AI features used by multiple teams and operating at Amazon scale.
• Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability.
• Collaborate with Product and Science to define experiences, run experiments, and iterate based on data.
• Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
• Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention.
• Navigate ambiguity and make sound technical decisions in a problem space where established patterns don't always apply.

Skills

Java

C++

C#

OO design

Full SDLC

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field

Tools

Git

CI/CD

Linux

Job description

Amazon Development Center (Tel Aviv) is seeking a Software Development Engineer to design and build AI-powered personalization features at Amazon scale. You will own end-to-end delivery from design to production, mentor juniors, and raise engineering standards across teams.

You will work with product and science to experiment, measure impact, and iterate on experiences such as personalized recommendations and explanations using LLMs.