Agentic AI Platform Architect Job Irving area,Texas USA,Software Development

10+ years software architecture experience with at least 3 years designing AI/ML platform systems, including hands‑on experience with LLM orchestration frameworks (Lang Chain, Lang Graph, 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/Type Script.
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.

Job Description

10 Years of Experience as an 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. Lang Graph CrewAI Semantic Kernel Auto Gen 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

10 years software architecture experience with at least 3 years designing AI/ML platform systems including hands‑on experience with LLM orchestration frameworks Lang Chain Lang Graph 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/Type Script.
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
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.

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