The Devices & Services – AI for Product Operations team is building the next generation of AI-powered tools that transform how Amazon brings devices to market. We sit at the intersection of generative AI, operational program management, and the full product development process — from Pre-concept through NPI (New Product Introduction) to Launch — for the world's most popular consumer electronics: Kindle, Tablet, Echo, Fire TV, and more.
As a Software Development Engineer on our AI team, you will design and build full-stack AI agents and digitized workflows that automate and accelerate Product Operations across Lab126. Think: AI agents that autonomously gather intelligence across disparate systems, generate executive briefings, triage program risks, and orchestrate cross-functional decisions — all running at Amazon scale.
Your work directly impacts how quickly and flawlessly Amazon launches new devices. You'll own the architecture and delivery of AI systems that compress weeks of manual program management into minutes of intelligent automation. From LLM-powered document generation to multi-agent orchestration pipelines, you'll build tools that program teams rely on to hit every milestone from concept to customer.
This is not a traditional software engineering role — you'll wear multiple hats across the full lifecycle of AI-native products. One week you're the Prototyper, rapidly experimenting with new agent architectures (many of which won't ship). The next you're the Builder, hardening a prototype into a production-grade system. Then you're the Grower, expanding a working agent to cover new workflows and teams. You'll work with the latest technologies including large language models, retrieval-augmented generation (RAG), agent frameworks, MCP (Model Context Protocol) servers, context and loop engineering, and internal Amazon AI infrastructure. You'll ship fast, iterate with real users, and see your work transform how an entire organization operates.
You'll collaborate directly with product and engineering leaders and senior leadership, have end-to-end ownership of systems, and operate with startup-level autonomy backed by Amazon's resources. If you want to build AI agents and digitized workflows that change the way an organization works — not research prototypes that sit on a shelf — this is the role.
Join us in redefining how Product Operations works in the age of AI, within one of the world's most innovative devices and services organizations.
Key job responsibilities
- Design and build AI agents and multi-agent orchestration systems that automate Product Operations workflows end-to-end
- Develop full-stack applications integrating LLMs, RAG pipelines, MCP servers, and internal Amazon data sources into production-grade tools
- Rapidly prototype new AI-powered solutions — validate with real users, iterate quickly, and know when to kill an experiment vs. scale it
- Build context engineering systems that give AI agents reliable access to enterprise knowledge across disparate platforms
- Collaborate with product and engineering leaders to identify high-impact automation opportunities across the product development lifecycle
- Own the full delivery cycle: architecture, implementation, deployment, and monitoring of AI systems in production
- Design evaluation frameworks to measure agent accuracy, reliability, and business impact
- Stay current with the fast-evolving AI landscape and translate breakthroughs into practical team capabilities
- Participate in code reviews, knowledge sharing, and technical documentation to elevate engineering standards
- Be flexible to attend meetings outside of regular business hours when collaborating with global teams
- Travel domestically and globally up to 10% of the time
A day in the life As an SDE on this AI-native team, your day is dynamic and growth-oriented. You might start with a team stand-up, then dive into coding a new AI agent that automates a workflow that used to take weeks. Mid-morning could see you demoing a prototype to leadership, getting real-time feedback. After lunch, you might pair with the AI lead, a product and engineering veteran, learning how to think end-to-end from problem to production. The afternoon could involve debugging a RAG pipeline, experimenting with a new model, or shipping a feature users want.
About the team We're an AI-native team, meaning AI isn't just what we build, it's how we work. Every member uses AI agents daily to amplify their output: researching, coding, writing, and decision-making. We believe the best AI products come from people who live inside them.
This is a team where an SDE learns product strategy, a PM writes code, and everyone ships. We deliberately break role boundaries because building AI for operations requires understanding operations deeply. You'll grow faster here than in a traditional engineering team — not just as an engineer, but as an AI builder who sees the full picture.
Basic Qualifications
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience in one of the following programming languages: Java, Python, Ruby, Node.js, C#, or C
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience working with REST API based services, or experience in deploying identity and access management systems and experience in software development
- Bachelor's degree in computer science, computer engineering, or related technical field
Preferred Qualifications
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience building applications with LLMs, prompt engineering, or AI/ML frameworks (e.g., LangChain, Bedrock, SageMaker)
- Experience with RAG architectures, vector databases, or knowledge retrieval systems
- Experience building or consuming MCP servers, AI agents, or multi-agent systems
- Familiarity with cloud-based services, particularly AWS infrastructure
- Strong written and verbal communication skills, with the ability to explain complex technical concepts to non-technical audiences
- Experience collaborating with product and program management teams
- Contributions to open-source projects or personal AI/automation projects demonstrating passion for the space
- Master's degree in Computer Science, Computer Engineering, or a related field
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.