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# DEVELOPER L4

- **Company:** Wipro Limited
- **Location:** Dallas, TX, United States
- **Experience:** Experienced
- **Salary:** $60,000.0 - $135,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Distributed Systems, Graph Database, Python (Programming Language), Software Architecture, Azure Machine Learning, Data Streaming, Systems Integration, TypeScript, Large Language Models, Multi-Agent Systems, Prompt Engineering, Togaf, AI Platforms, Kubernetes, Machine Learning Operations, Virtual Agents, Api Design, Grpc, Api Management, Microservices
- **Published:** June 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=288402080733a192

## About the Role

Do you have experience in System design?, 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.

Mandatory Skills: AI Azure ML Document Intelligence .

Experience: 5-8 Years .

## Description

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.


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