Principal Solution Architect Agentic AI Platform- w2 contract

Role: Principal Solution Architect 10924

Dallas Forth worth, TX – Hybrid

Duration: 6 months+

Rate: Contract on  W2

Interview: 2 round F2F (onsite interview/Glider Test)

10 Years of Experience as a 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

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/Google Cloud Platform 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.

Regards,

Shawn Davis,

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