About The Position

The Amazon Devices Reverse Logistics (ADRL) team seeks an Analytics Engineer specializing in AI-augmented analytics – You'll pioneer intelligent agentic systems by building multi-agent frameworks that enable natural language querying, automated insight generation, and intelligent workflow orchestration. You'll establish a curated, certified foundational data layer with robust governance, making Reverse Logistics data seamlessly accessible to AI tools and customers. The ideal candidate combines expertise in generative AI, machine learning, and modern BI engineering—architecting solutions that unlock advanced analytical capabilities while maintaining enterprise-grade quality, security, and scalability. A day in the life You leverage AI-powered tools like Amazon Quick Suite and Kiro to accelerate BI solution development through natural language queries and automated code generation. You build and maintain scalable ETL pipelines and semantic data models feeding traditional dashboards and AI-driven products while ensuring data quality through AI-assisted monitoring. You partner with Strategy, Product, and Data Engineering & Science stakeholders to translate business questions into structured solutions using rapid prototyping. You experiment with emerging AI/ML tools and agentic frameworks, evaluating capabilities like natural language querying, automated anomaly detection, and AI-assisted monitoring. You present findings through interactive dashboards and proof-of-concepts, communicating both value and limitations to technical and non-technical stakeholders. About the team The Amazon Devices Reverse Logistics (ADRL) team builds and sustains the global Amazon Device Reverse Supply Chain (RSC). ADRL processes ~7M returns annually, fulfills 1M warranty replacement requests from customers, and delivers 2M certified refurbished devices to pre-owned customers with an annual growth rate of 10%. The RL BI (Analytics) team owns the data and reporting ecosystem for the RL business, delivering high-grade, certified data solutions that enable confident business decisions with superior data quality and integrity.

Requirements

  • 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • 3+ years of processing large, multi-dimensional datasets from multiple sources experience
  • Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Proficiency with AI tools and platforms – Building multi-agent systems using TensorFlow, PyTorch, LangChain, and AutoGen; integrating generative AI and LLMs; applying reinforcement learning and optimization algorithms
  • Experience with AWS DevOps/AI/ML services – Deploying and working with intelligent agentic RAG applications using SageMaker, Bedrock, and Lambda
  • Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
  • Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage

Nice To Haves

  • Experience in Statistical Analysis packages such as R, SAS and Matlab

Responsibilities

  • Build and evolve AI-driven analytics platform for ADRL organization – Develop intelligent systems using multi-agent frameworks that enable natural language querying, automated insight generation, and workflow orchestration to accelerate delivery, reduce manual effort, and scale BI solutions
  • Design and deploy agentic solutions for Reverse Logistics Business – Leverage Python and AWS services (SageMaker, Bedrock, Lambda) to build intelligent automations for business workflows with real-time insights, delivering predictive recommendations, actionable insights, and proactive alerts to executive leadership
  • Curate foundational data layers and implement governance frameworks – Enable AI tools to leverage high-quality, semantically modeled data for business decision-making across ADRL
  • Partner with Data Engineering and Applied Science teams – Enhance data sources and analytics processes, explore AI/ML integration opportunities for more scalable and accurate reporting, and translate business requirements into scalable automated solutions
  • Create multi-agent frameworks serving as self-service hubs – Enable tailored querying and analytics access for all RL stakeholders across organizational data
  • Document patterns and establish guidelines for responsible AI use – Implement best practices for model monitoring, A/B testing, and continuous improvement

Benefits

  • Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave.
  • Learn more about our benefits at https://amazon.jobs/en/benefits
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