Senior Software Engineer, Frontier AI

- 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
- 5+ 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

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USA, WA, BELLEVUE - 168,100.00 - 227,400.00 USD annually
The Data processing team is part of Amazon's Frontier AI organization, focused on building the foundational data infrastructure that powers next-generation AI/ML models. We are responsible for designing and implementing large-scale data pre-processing pipelines that transform data into high-quality training datasets. Our work directly impacts the performance and capabilities of frontier AI systems.

We are looking for a talented and experienced Software Development Engineer to join the team and lead the design, development, and optimization of data pre-processing systems at scale with automated benchmarking. In this role, you will develop scalable data infrastructure to support the preparation and delivery of high-quality datasets for AI and machine learning applications. You will work at the intersection of distributed systems, data engineering, and machine learning to solve some of the most challenging data problems in AI.

Key job responsibilities
- Design and build scalable data pre-processing pipelines that handle petabyte-scale datasets across diverse modalities (text, code, structured data, etc.)
- Develop data quality frameworks including deduplication, filtering, toxicity detection, PII removal, and content classification
- Optimize pipeline performance for throughput, latency, and cost-efficiency across distributed compute environments
- Define and implement data transformation logic such as tokenization, normalization, formatting, and schema standardization
- Collaborate with Scientists to understand data requirements and translate them into engineering solutions
- Own end-to-end system design from architecture through deployment, monitoring, and operational excellence
- Drive technical decisions and influence the team's roadmap through design documents, code reviews, and mentorship
- Establish best practices for data lineage, versioning, reproducibility, and auditability of training data
- Mentor junior engineers and raise the technical bar across the team