Senior Software Engineer Agentic AI, Amazon's Talent Solution’s Core Science and Engineering

Overview

Join Amazon's Talent Solution’s Core Science and Engineering organization as a Senior Software Development Engineer at the forefront of talent evaluation and development for the world's most customer obsessed Join Amazon's Talent Solution’s Core Science and Engineering organization as a Senior Software Development Engineer at the forefront of talent evaluation and development for the world's most customer obsessed co

What you'll do

• Join Amazon's Talent Solution’s Core Science and Engineering organization as a Senior Software Development Engineer at the forefront of talent evaluation and development for the world's most customer obsessed Join Amazon's Talent Solution’s Core Science and Engineering organization as a Senior Software Development Engineer at the forefront of talent evaluation and development for the world's most customer obsessed company.
• This highly visible role will shape the future of Amazon's talent using advanced machine learning and agentic AI technologies and by partnering directly with PXT (People Experience and Technology) and Amazon leadership to drive transformative initiatives, operational excellence, and strategic innovation.
• You'll have the unique opportunity to influence how hire and develop the best across all of Amazon's businesses across the globe.
• Our team builds distributed, scalable, and highly available systems that make Machine Learning (ML), LLM, Econometrics/Statistical/Causal models run faster in a CI/CD fashion.
• We own products ranging from Data Lakes to tools for science experimentation, MLOps, GenAIOps, and analytics to web applications and software solutions integrated with other Amazon systems.
• Robust and user-friendly software solutions, and data security and privacy are our top concerns.
• We're seeking a Software Development Engineer (SDE) specializing in managing large volumes of data within an MLOps/GenAIOps framework.
• Desired expertise includes familiarity with Machine Learning lifecycle management, encompassing model training, validation, debugging tools, analysis techniques, and enhancing LLM responses through methodologies like RAG, Prompt Engineering.
• The perfect fit will possess robust software engineering fundamentals, adeptness in system architecture, a strong grasp of machine learning principles, and the capability to construct scalable systems that streamline model deployment and GenAI application building.
• Exposure to ML system design, frameworks, GenAI application design/development and industry best practices would be advantageous.

Requirements

• Practical experience with LLM, RAG, Machine Learning, Scala.
• Experience level: 5+ yrs.
• Strong written and verbal communication in English.
• Comfortable working on-site in Bellevue, Washington, USA.

Skills