We are looking for a Senior Project Manager to join an enterprise AI Center of Excellence (AI CoE) within a large airline environment. This individual will lead the delivery of strategic AI and Generative AI initiatives, with a strong emphasis on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and enterprise AI platforms.
This role will partner with AI/ML engineers, data scientists, software engineers, architects, product leaders, cybersecurity teams, business stakeholders, and external vendors to move AI solutions from proof of concept through production deployment and enterprise adoption.
This is not a hands-on AI engineering role; however, the ideal candidate must possess a strong working knowledge of LLM and RAG architectures and be comfortable leading technical discussions involving vector databases, embeddings, prompt engineering, model evaluation, data pipelines, AI governance, and responsible AI. This person will also help the AI CoE establish repeatable delivery frameworks, standards, and governance practices that enable AI adoption across the organization.
Key responsibilities:
- Lead the end-to-end delivery of AI and Generative AI initiatives, from use-case discovery and proof of concept through production deployment and ongoing optimization.
- Manage multiple initiatives involving LLMs, RAG, AI agents, conversational AI, intelligent search, document processing, and workflow automation.
- Partner with AI/ML engineers, data scientists, architects, application teams, and business stakeholders to define scope, milestones, dependencies, risks, and success criteria.
- Drive project execution using Agile delivery methodologies and Jira, including backlog management, sprint planning, RAID tracking, schedules, and delivery reporting.
- Coordinate the delivery of RAG-based solutions involving enterprise data sources, embeddings, vector databases, retrieval strategies, prompt orchestration, and LLM-generated responses.
- Facilitate cross-functional technical and business discussions and ensure alignment between the AI Center of Excellence and business teams.
- Oversee testing, model evaluation, production readiness, security, data privacy, governance, and release planning for AI solutions.
- Identify and manage AI-specific risks, including hallucinations, model quality, bias, privacy, data quality, security, and regulatory concerns.
- Prepare and communicate project status, risks, dependencies, KPIs, roadmaps, and executive-level updates to key stakeholders.
- Support the development of repeatable AI delivery frameworks, governance standards, and best practices across the organization.
- Coordinate external vendors, cloud providers, consulting partners, and internal delivery teams as needed.
- Drive change management, user readiness, training, adoption, and measurement of business outcomes for AI-enabled solutions