About the job
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.
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
Qualifications
Minimum
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 in Statistical Analysis packages such as R, SAS and Matlab
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
Preferred
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.