Description

Required:

• 10+ years of software architecture or senior engineering experience.
• At least three years of experience designing AI/ML platform systems.
• Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, or similar technologies.
• Proven experience building and deploying agentic AI systems or LLM-powered applications at production scale.
• Strong knowledge of multi-agent orchestration and agent tool-use patterns.
• Experience designing RAG pipelines and prompt-engineering solutions.
• Strong understanding of agent reliability, observability, evaluation, security, and guardrails.
• Deep expertise in distributed systems, microservices architecture, and event-driven design.
• Strong API design experience using REST and/or gRPC.
• Advanced programming skills in Python.
• Proficiency in at least one additional language: Java, Go, or TypeScript.
• Ability to evaluate technical tradeoffs and clearly communicate architectural decisions.
• Experience leading technical reviews and mentoring engineering teams.

Preferred:

• Kubernetes and container-orchestration experience.
• Experience with AWS, Azure, or Google Cloud Platform.
• Knowledge of MLOps and LLMOps tools and practices.
• Experience with vector databases such as Pinecone, Weaviate, or pgvector.
• Knowledge of graph databases or knowledge graphs.
• Experience designing multi-agent system patterns.
• Familiarity with agent evaluation and benchmarking frameworks.

Responsibilities:

• Define and evolve the architecture of American Airlines’ Agentic System Layer.
• Design multi-agent orchestration systems, tool-use frameworks, and LLM integration pipelines.
• Establish enterprise patterns for agent reliability, observability, security, guardrails, and graceful degradation.
• Design scalable distributed systems using microservices and event-driven architecture.
• Define REST and gRPC API contracts, data-flow patterns, and integration standards across the AI platform.
• Build and improve RAG pipelines, prompt-management solutions, tool-calling patterns, and LLM-routing strategies.
• Evaluate and integrate agentic AI frameworks such as LangGraph, LangChain, CrewAI, Semantic Kernel, and AutoGen.
• Lead technical design reviews and create Architecture Decision Records (ADRs).
• Collaborate with software engineers, ML engineers, and architects to deliver scalable, secure, and maintainable platform components.
• Develop code and proof-of-concept solutions to validate architectural decisions.
• Support platform development, feature delivery, and production operations.
• Participate in Agile ceremonies, architecture discussions, and code reviews.
• Mentor engineers on best practices for developing production-grade AI systems

Key Skills

Education

Bachelor's degree