Machine Learning Architect – LLM & Agentic AI (RAG Systems)

About the Role

As a Machine Learning Engineer on the Agentic System Layer (ASL) team, you will build the ML-powered components that make American Airlines’ agentic AI systems intelligent and reliable.

Responsibilities

• Develop and optimize LLM-powered agent pipelines including prompt engineering, chain-of-thought reasoning, and tool-use patterns
• Build RAG (Retrieval Augmented Generation) systems with vector search, embedding models, and knowledge retrieval pipelines
• Implement agent evaluation, benchmarking, and regression testing frameworks
• Fine-tune and optimize model inference for latency and cost (quantization, caching, batching, model routing)
• Develop guardrails, content filtering, and safety mechanisms for production agent deployments
• Collaborate with software engineers on model serving infrastructure and with architects on system design
• Stay current with rapid advances in agentic AI, LLM capabilities, and evaluation methodologies

About You

A great candidate lives at the intersection of ML research and production engineering. They can read the latest papers on agentic AI, understand what is practically useful versus academic noise, and turn those ideas into production-ready code. They obsess over evaluation - they know that if you cannot measure it, you cannot ship it. They are comfortable with the inherent non-determinism of LLM systems and have practical strategies for building reliability on top of probabilistic foundations.

Work Arrangement

Candidate will be working hybrid; onsite 3 days a week and 2 days virtually.

Pre-assessment Test

Required

Interview Process

In-person Interview