AI Architect

Cloudious LLC; Dallas (TX); Hybrid; USD 170,000 - 230,000; Full time

Job summary

American Airlines' AI Platforms Capabilities team seeks a seasoned software architect to design and deploy agentic AI systems at scale. The role focuses on multi-agent orchestration, LLM routing strategies, and ensuring production readiness with observability.

The embedded squad works hybrid from the DFW area, collaborating with engineers and ML experts to deliver reliable platform capabilities and rapid iteration in a fast-paced environment.

Qualifications

• 10+ years of software architecture experience with AI/ML platform design.
• Hands-on with LLM orchestration frameworks (LangChain, LangGraph, Semantic Kernel or similar).
• Deep expertise in distributed systems, microservices, event-driven patterns and API design (REST/gRPC).
• Production experience building agentic AI systems at scale, including prompt engineering and RAG pipelines.

Responsibilities

• Whiteboard multi-agent orchestration designs and evaluate LLM routing strategies.
• Implement code to prove design decisions and ensure reliability and observability.
• Collaborate with architects, engineers, and ML engineers in agile, hybrid environment.

Skills

Software architecture

LLM orchestration

Python

Job description

Top 3 Mandatory Skills and Experience:

• 10+ years software architecture experience with at least 3 years designing AI/ML platform systems, including hands-on experience with LLM orchestration frameworks (LangChain, LangGraph, Semantic Kernel, or similar).
• Deep expertise in distributed systems design, microservices architecture, event-driven patterns, and API design (REST/gRPC), with strong proficiency in Python and at least one of Java/Go/TypeScript.
• Production experience building and deploying agentic AI systems or LLM-powered applications at scale, including prompt engineering, tool-use patterns, RAG pipelines, and agent reliability/observability.

Nice to Have Skills:

• Experience with Kubernetes/container orchestration, cloud platforms (AWS/Azure/GCP), MLOps/LLMOps tooling, vector databases (Pinecone, Weaviate, pgvector), knowledge graphs, airline/travel domain experience, TOGAF or similar architecture certification, experience with multi-agent system design patterns and agent evaluation/benchmarking frameworks.

What Makes a Great Candidate?

A great candidate is a seasoned architect who has shipped production agentic AI systems - not just prototypes. They can whiteboard a multi-agent orchestration system, debate tradeoffs between different LLM routing strategies, and then jump into code to prove out a design. They understand that agentic systems at airline scale need bulletproof reliability, graceful degradation, and real observability. They have opinions backed by experience, they push back on bad ideas constructively, and they make the engineers around them better.

What is the team environment and structure like?

The AI Platforms Capabilities team builds and operates the Agentic System Layer (ASL), which is American Airlines' core platform for deploying agentic AI systems. The team operates in an agile environment with a focus on rapid iteration, production reliability, and close collaboration between architects, engineers, and ML engineers. The team works hybrid from the DFW office.

The resource will be embedded directly into the ASL squad, working alongside full-time engineers and architects on platform development, feature delivery, and production support. They will participate in sprint ceremonies, code reviews, and architecture discussions.