GenAI / NLP Engineer

GenAI / NLP Engineer – Multi Agent AI Platforms (Network Planning) Chicago-based, onsite 2–3 days per week (approximately 5–6 days per month minimum) 15 month contract + Overview Network Planning team within the Commercial Systems portfolio is launching a GenAI Enablement Initiative to enhance decision support, insight generation, and usability of planning data and models. This role will support the design and delivery of a scalable, cloud-based multi-agent GenAI platform integrated with United’s enterprise AI/ML ecosystem (MARS). The successful candidate will contribute to building a supervisory chatbot and specialized AI agents that deliver insights, diagnostics, workflow guidance, and automated reporting for Network Planning stakeholders. This is a net-new role supporting a growing GenAI capability. Key Responsibilities GenAI Platform & Architecture • Design and build an end-to-end, multi-agent GenAI architecture integrated with United’s MARS platform, enterprise GenAI tooling, and existing ML infrastructure. • Develop a supervisory/orchestrator chatbot that routes user requests to specialized downstream agents. • Design modular, extensible AI agents to support evolving business use cases. • Ensure response traceability, accuracy, and adherence to Responsible AI, security, and governance standards. • Collaborate closely with Network Planning, MARS platform, Cloud Engineering, and Security teams. Agent & Use Case Development Deliver initial use cases end-to-end into production, while creating a reusable foundation for future expansion: Use Case 1: Network Planning Knowledge Assistant (Supervisory Chatbot) • Embed an AI-powered chatbot within the Network Planning MediaWiki UI. • Enable users to understand terminology, navigate applications, and retrieve knowledge. • Leverage MediaWiki content as a knowledge base using NLP/LLM techniques. • Provide contextual, explainable responses with links to source content. Use Case 2: Automated Capacity & Schedule Summary Agent • Ingest recurring airline capacity and schedule reports (e.g., PDFs). • Generate executive-ready weekly summaries of network changes. • Surface insights and recommendations (e.g., increase or reduce capacity, airline participation). • Implement approval workflows prior to report distribution. Planned Future Use Cases • Diagnostic analyst agents (“why did the model produce this output?”). • “What-if” scenario and planning workflow agents. • Guided parameter tuning and optimization support. Engineering & Operations • Build required data pipelines, retrieval mechanisms, and system integrations for each agent. • Participate in testing, validation, and production deployment using United’s established MLOps and GenAI frameworks. • Support continuous improvement, automation, and onboarding of additional agents as the ecosystem grows. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Required Skills & Experience Must-Haves • Experience architecting and building GenAI and NLP applications, ideally using multi-agent or agent-orchestrated patterns. • Hands-on experience integrating LLMs and GenAI solutions into production enterprise environments. • Proficiency in Python; Julia experience strongly preferred (or willingness to ramp quickly). • Experience working with existing enterprise AI/ML platforms (non-greenfield builds). • Strong problem-solving skills with the ability to work independently in ambiguous environments. Nice to Have • Background in machine learning or ML-driven applications. • Experience with cloud-based architectures (AWS preferred). • Familiarity with model diagnostics, explainability, or decision-support systems. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Soft Skills & Expectations • Highly independent, driven, and proactive. • Strong communication skills, particularly the ability to explain GenAI concepts and outputs to non-technical stakeholders. • For senior candidates: serve as the primary GenAI thought leader, guiding design decisions and mentoring less experienced team members.