Position Overview
We are seeking an experienced Senior AI Software Engineer (based in Chicago, IL) with a strong background in building production-grade generative AI applications, agentic workflows, and custom tool integrations. In this role, you will design, architect, and deploy advanced AI systems leveraging modern frameworks like LangGraph and Model Context Protocol (MCP).
A strong preference will be given to candidates with prior engineering or consulting experience within the aviation, travel, or airline industry (specifically United Airlines), enabling them to hit the ground running with complex industry constraints, legacy system integrations, and enterprise security standards.
Key Responsibilities
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Architect Agentic Workflows: Design and implement multi-agent architectures and complex stateful workflows using LangGraph and advanced orchestration patterns.
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Build Custom Tooling: Develop, secure, and integrate custom tools using Model Context Protocol (MCP) and robust Python APIs to connect LLMs with enterprise data sources and internal applications.
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Core Development: Write clean, scalable, and maintainable Python code for backend AI microservices, RAG pipelines, and model evaluation harnesses.
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Enterprise Integration: Collaborate with cross-functional stakeholders (Security, Legal, Engineering) to deploy AI solutions that adhere to strict corporate compliance and data governance standards.
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Performance & Scale: Optimize latency, token usage, and cost-efficiency for production LLM deployments handling high-volume enterprise traffic.
Qualifications & Requirements
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Location: Must be based in Chicago, IL (or local by day one).
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Technical Expertise:
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4+ years of professional software engineering experience with advanced proficiency in Python.
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Demonstrated production experience building agentic applications using frameworks like LangGraph, LangChain, or AutoGen.
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Hands-on experience implementing and extending Model Context Protocol (MCP) servers, custom tool-use loops, and function calling.
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Deep familiarity with LLM providers, vector databases, RAG architectures, and asynchronous programming in Python.
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Industry Experience:
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Strong preference for candidates with previous United Airlines or major airline/aviation tech experience, particularly familiarity with internal enterprise systems, operational workflows, or commercial aviation products.
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Collaboration & Delivery:
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Experience working in agile, fast-paced environments with a track record of taking AI projects from prototype to production.
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Strong communication skills with the ability to bridge technical AI mechanics and business value for leadership and stakeholders.
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