AWS AI Engineer / USC and GC Candidates can ONLY Apply
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About the role
We are hiring a Sr AI AWS Engineer who has actually built AI/ML applications in cloud—not just read about them. This role centers on hands-on development of retrieval-augmented generation (RAG) systems, fine-tuning LLMs, and AWS-native microservices that drive automation, insight, and governance in an enterprise environment. You’ll be part of a high-impact team pushing the boundaries of cloud-native AI in a real-world enterprise setting. This is not a prompt-engineering sandbox or a resume keyword trap. If you’ve merely dabbled in BedRock, mentioned RAG on LinkedIn, or read about vector search—this isn’t the right fit. We’re looking for candidates who have architected, developed, and supported AI/ML services in production environments. This is a builder’s role within our Public Cloud AWS Engineering team. We aren’t hiring buzzword lists or conference attendees. If you’ve built something you’re proud of—especially if it involved real infrastructure, real data, and real users—we’d love to talk. If you’re still learning, that’s great too—but this isn’t an entry-level role or a theory-only position.
What you'll bring
- 7 years of hands-on software engineering experience with a strong focus on Python.
- AWS or relevant cloud certifications
- Data privacy and compliance best practices (e.g., PII handling, secure model deployment)
- Data science background or experience working with structured/unstructured data
- Exposure to FinOps and cloud cost optimization
- Hugging Face, Node.js
- Policy as Code development (I.e.
- Terraform Sentinel)