Software Dev Engineer II, Stores Foundational AI -SFAI

Amazon is hiring a Software Dev Engineer II, Stores Foundational AI -SFAI in Seattle, United States. It pays $144k-$194k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Tools and skills the posting cites include vLLM, PyTorch and JAX.
Level classifies it as a mid-level role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Build large-scale training and reinforcement learning infrastructure for generative AI models powering Amazon shopping.

vLLMPyTorchJAXPythonCUDA

fine-tuningmachine-learningreinforcement-learningdistributed-systemslarge-language-models

We’re working to improve shopping on Amazon using the capabilities of large language models (LLM), and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists and engineers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

Key job responsibilities
Key job responsibilities
In this role you will leverage both your engineering and machine learning background to help develop generative AI for shopping. On a day-to-day basis, you will:
- Design and implementation of a stable and efficient training system for model training and reinforcement learning that scale to various of model sizes and architecture.
- Collaborate with other talented applied scientists and engineers to improve training efficiency and reliability that accelerates innovation.
- Design and implement scalable data infrastructure: that handle Amazon-scale data ingestion, processing, and delivery across different training and evaluation stages;
- Quickly learn and adopt state-of-the-art technologies and algorithms in the field of Generative AI.

A day in the life
On any given day, you may work on:
Design and build end-to-end RL post-training pipelines (rollout → reward → optimization) at cluster scale
Improve RL training stability (PPO / GRPO / RLOO) by monitoring and tuning key metrics such as reward, KL divergence, and policy stability
Optimize RL post-training efficiency (GPU utilization, batching, sequence packing, async rollouts)
Partner with research scientists to translate new RL algorithms into scalable, production-ready systems
Profile and eliminate bottlenecks across compute, networking, and storage
Build observability systems for training dynamics, system health, and experiment tracking
Collaborate cross-functionally to run experiments, iterate quickly, and unblock research progress
Contribute to system design and long-term technical roadmap

About the team
The SFAI Training Infrastructure team builds a unified platform for large-scale LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine learning, building a platform that is:

Scalable — Efficiently train modern model architectures across large-scale compute environments
Reliable — Enable long-running jobs through fault tolerance, monitoring, and automated recovery
Efficient — Maximize hardware utilization and throughput through system-level optimizations
Simple and Unified — Provide a consistent, config-driven interface across models and workflows

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 programming with at least one software programming language
- Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques

Preferred qualifications

- Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
- Knowledge of system performance, memory management, and parallel computing principles
- Experience with CUDA/C++/Kernel development

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. 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.

USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually

How we rate this

Software Dev Engineer II, Stores Foundational AI -SFAI at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Software Dev Engineer II, Stores Foundational AI -SFAI is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $144k-$194k a year.
The role is based in US, WA, Seattle.
The job was posted on June 10, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningMachine learningReinforcement learningDistributed SystemsLarge Language ModelsvLLMPyTorchJAX

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where reinforcement learning was part of your work. What did you do?
Tell me about a project where distributed systems was part of your work. What did you do?
Tell me about a project where large language models was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Fine-tuning, Machine learning, Reinforcement learning, Distributed Systems, and Large Language Models. 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.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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