Principal Solution Architect

Principal Solution Architect

7-12+ Months contract

Fort Worth, TX (In-person interview)

As Sr Eng 2 Architect on the Agentic System Layer (ASL) team, you will define and drive the technical architecture for American Airlines’ agentic AI platform. Day-to-day responsibilities include: designing and evolving the architecture for multi-agent orchestration systems, tool-use frameworks, and LLM integration pipelines; establishing patterns for agent reliability, observability, and guardrails at production scale; leading technical design reviews and producing architecture decision records (ADRs); collaborating with ML engineers and software engineers to ensure platform components are scalable, secure, and maintainable; evaluating and integrating emerging agentic AI frameworks (e.g., LangGraph, CrewAI, Semantic Kernel, AutoGen); defining API contracts, data flow patterns, and integration standards across the AI platform ecosystem; mentoring engineers on best practices for building production-grade AI systems.

Top 3 Mandatory Skills and Experience:
1) 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).
2) 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.
3) 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.

NOTE:

• These candidates need to be experts in engineering, architecture.
• Project: AI Engineering team - take care of running agents for different domains. Focused on building agents - for commercial: for customers, messages, etc.
• D2D: design, understand business requirements, develop the multi- or single agents. 
• not just APIs, semantic script, work with agents
• agents: develop workflow to automate, framework - needs to know which to use, which tools to access depending on the requirements needed
• what they're looking for: 
• exp with frameworks like LangGraph**, LangChain, or something similar
• knows to evaluate an agent not just build it
• design the governance: they need to know context of the agent, how it fits the architecture
• Can speak about the fundamentals - difference of tools and how they use it. 
• Not a data engineer/data scientist or engineer with just java/python exp.