Senior Software Development Engineer , Stores Foundational AI - Rufus
Amazon · Palo Alto, CA · Software Development
senior
Software Engineer
ic
· Posted Mar 9, 2026
$193,300 – $261,500
USD per year
Skills
About this role
Amazon is hiring a senior-level Software Engineer based in Palo Alto, CA. The posting calls out experience with CUDA, LLMs, Reinforcement Learning, Distributed Systems. Compensation is listed at $193,300–$261,500 per year.
- Role
- Software Engineer
- Function
- software engineering
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Palo Alto, CA
- Department
- Software Development
- Posted
- Mar 9, 2026
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Job description
from Amazon careersWe are building foundational LLMs for Amazon Stores that fuse world knowledge with deep e-commerce understanding to power next-generation shopping experiences. These systems continuously learn from real-world customer interactions to become more helpful, personalized, and context-aware over time.
We are looking for builders who are passionate about large-scale systems, AI innovation, and customer impact. You will work at the intersection of distributed systems, machine learning infrastructure, and science to bring frontier research—especially in post-training and reinforcement learning—into production at Amazon scale.
Key job responsibilities
* Architect and build scalable ML infrastructure powering LLM training and post-training workflows, including supervised fine-tuning, reinforcement learning, and continuous learning from live traffic
* Transform real-world customer interactions into high-quality training signals, enabling continuous model improvement and better customer experiences
* Build and optimize post-training and RL systems, including reward modeling, policy optimization, data collection loops.
* Drive experimentation and iteration velocity by building tooling and frameworks that enable rapid hypothesis testing, signal validation, and model quality improvements
* Partner closely with applied scientists to translate frontier techniques (e.g., RLHF, agentic workflows, multi-turn optimization) into reliable, production-grade systems
* Own systems end-to-end, including design, implementation, deployment, observability, and operational excellence
* Raise the engineering bar through technical leadership, design reviews, and mentorship, influencing best practices across the organization
We are looking for builders who are passionate about large-scale systems, AI innovation, and customer impact. You will work at the intersection of distributed systems, machine learning infrastructure, and science to bring frontier research—especially in post-training and reinforcement learning—into production at Amazon scale.
Key job responsibilities
* Architect and build scalable ML infrastructure powering LLM training and post-training workflows, including supervised fine-tuning, reinforcement learning, and continuous learning from live traffic
* Transform real-world customer interactions into high-quality training signals, enabling continuous model improvement and better customer experiences
* Build and optimize post-training and RL systems, including reward modeling, policy optimization, data collection loops.
* Drive experimentation and iteration velocity by building tooling and frameworks that enable rapid hypothesis testing, signal validation, and model quality improvements
* Partner closely with applied scientists to translate frontier techniques (e.g., RLHF, agentic workflows, multi-turn optimization) into reliable, production-grade systems
* Own systems end-to-end, including design, implementation, deployment, observability, and operational excellence
* Raise the engineering bar through technical leadership, design reviews, and mentorship, influencing best practices across the organization
Basic Qualifications
This is an excerpt. Read the full job description on Amazon careers →