Sr Software Dev Engineer, Stores Foundational AI -SFAI

Amazon • Palo Alto, CA

1d • Hybrid

About The Position

Join us in building the systems that enable Amazon’s AI models to learn from
real-world customer behavior and continuously evolve at massive scale.

We are seeking a Senior Software Development Engineer to architect and own
large-scale training data systems and experimentation frameworks that power
Amazon’s next-generation shopping AI. This is a hybrid role that combines
distributed systems engineering with strong data science rigor to transform
customer interactions — including search refinement, clicks, add-to-cart, and
purchase behavior — into measurable learning signals that improve the shopping
experience for Amazon customers.

You will build scalable, production-grade systems that convert live traffic into
structured datasets used in model training and post-training workflows. Beyond
infrastructure, you will analyze model behavior, generate insights into model
quality gaps, and refine training data recipes to ensure durable, high-impact
improvements. Your work will directly shape how AI systems continuously evolve
from real customer behavior.

This role sits at the intersection of ML infrastructure, data science, and
production systems, with end-to-end ownership from data ingestion to training
data recipe design.

Requirements

• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience as a mentor, tech lead or leading an engineering team
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience working with scientists, economists, software developers, or product managers
• Solid understanding of statistics and experience analyzing model behavior to inform training data improvements

Nice To Haves

• Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in machine learning, data mining, information retrieval, statistics or natural language processing
• Experience using business metrics and training data to track, trend, and manage the impact of training efforts
• Experience designing or refining training data recipes to improve model performance
• Experience working with live production traffic data and behavioral signals
• Strong understanding of data governance, privacy, and security best practices

Responsibilities

• Architect scalable training data systems that enable AI models to continuously learn from live customer behavior
• Build high-throughput pipelines that transform production engagement signals into structured training datasets
• Analyze model behavior to generate insights into model quality and identify gaps in training data coverage
• Design and refine training data recipes, including sampling strategies, signal weighting, filtering, and dataset composition
• Apply statistical rigor and experimentation to validate training signal quality and model improvements
• Ensure strong data security, governance, and compliance standards across production data workflows
• Provide technical leadership across distributed systems and ML training infrastructure

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed