AmazonPosted today
Software Development Engineer II, FBA Capacity and Inventory Health Management
Software Development Engineer II, FBA Capacity and Inventory Health Management at Amazon scores 65 out of 100 on AI centrality, which makes it a Level 3 role on this board.
AI in this role
Build native-AI distributed software services and capacity management tools for Amazon's FBA ecosystem.
Key job responsibilities
You will leverage Native-AI development across SDLC. You design at the product level with heavy involvement through all phases of the SDLC using concepts that may include Service Oriented Architecture, caching, load balancing, non-relational databases, microservices, sharding, n-tiered architecture, cloud and/or map-reduce.
You use object-oriented design concepts to program large multi-tier systems. You have working knowledge of common and useful design patterns.
You have designed, refactored, re-architected, deprecated and/or implemented large-scale cloud-based distributed services with millisecond latency and ultra-high transactional volumes.
You have experience implementing best practices in improving team coding culture subjected related to quality and/or security
Effectively articulate technical challenges and solutions to non-technical audiences.
In this job, you will…
Build Native-AI software products for Amazon's WW Selling partners.
Experiment with whatever technology we need to get the job done.
Use Lean Software Development concepts such as Agile, Scrum and Kanban.
Use Test-Driven Development and Continuous Deployment.
Work with Senior and Principal Engineers, Researchers, and Data Engineers across multiple teams to design a new platform for optimizing supply chain management
Expand and optimize our world-class supply chain systems to support a variety of emerging business initiatives.
Automate third party supply management systems and break new ground to drive inventory across Amazon marketplaces.
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
- 3+ years of Video Games Industry (supporting title Development, Release, or Live Ops) experience
- Experience programming with at least one software programming language
Preferred qualifications
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
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.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where software development was part of your work. What did you do?
- Tell me about a project where object oriented design was part of your work. What did you do?
- Tell me about a project where cloud computing was part of your work. What did you do?
- Tell me about a project where system architecture was part of your work. What did you do?
- Walk me through how you've used Native AI in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Software Development, Object Oriented Design, Cloud Computing, System Architecture, and Native AI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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