IT Manager (AI)

Responsibilities:
Exhibits strong business and leadership skills, a deep technology perspective to guide solutions, and strong communication skills to coordinate with engineers to ensure they understand business needs and objectives, as well as the technical requirements of products.
Collaborates with business and IT leadership to execute and communicate the organization's technical vision, mission, and work priorities, and drives progress towards roadmaps and ensures efficient technical product management and effective communication with stakeholders.
Creates an environment for delivery teams to be self-governing organizations that are accountable for their own performance and delivery commitments and measured accordingly.
Removes roadblocks, cultivates relationships, and effectively communicates across IT and at various levels of leadership.
Removes squad impediments and emphasizes cross-functional collaboration between roles.
Provides input on technology decisions, people management, and product features across all stages of the product lifecycle.
Establishes open lines of communication between engineering squads and IT leadership and supports clear adherence to business requirements.
Facilitate and monitor clear engineer check-ins, sprint deliverables, and open communication toward squads and stakeholders.
Drive forward increased technical upskilling across the organization with education, programs, and metrics.
Manage engineer staffing strategy to ensure alignment to Scrum and Agile principles and work closely with the Scrum Lead.
Promotes use of industry-leading technology trends and continuously assesses AA IT needs and areas for improvement.
Manages and leads adoption and migration of new and emerging technologies.
Leads, develops, and mentors a high-performing engineering team of individuals with a diverse range of technical skills and experiences.
Exhibits a desire for continuous learning and sharing of new knowledge within the organization.
Responsible for the hiring and management of squad members, including staffing and performance reviews as well.
Responsible for budget management and forecasting.
Manages production issues and off-hours support, communication, and coordination, as needed.
Works extended hours occasionally, based on the needs of the project and the operation.
Requirements:
Skills Required: Python, MLOPS, ML Engineering, Machine Learning Engineering, PyTorch, TensorFlow, RAG, LLM, AI Model.
Bachelor's degree in technology, computer science, information systems, or a related technical discipline, or equivalent experience/training.
9+ years of experience participating in delivery of solutions using ITIL / Agile / XP, or similar methodologies.
Airline industry experience, including engineering/business processes and supporting technology.
Skills, Licenses, and Certifications:
Experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, or Keras.
Experience implementing MLOps platforms, practices, and tools across the development lifecycle.
Experience developing and implementing generative AI solutions using Large Language Models (LLMs) (e. g., OpenAI GPT, Google Gemini, Llama).
Proficiency in Retrieval Augmented Generation (RAG) techniques for generative-based AI models.
Experience developing and implementing governance frameworks and controls for responsible AI.
Experience in cloud platform engineering for AI/ML.
Proven track record in leading engineering initiatives that generate substantial value; well-organized, able to multitask, and able to prioritize with minimal direction.
Strong technical leadership and extensive experience in Agile methodology-style leadership environments.
Excellent communication skills to present to executive management often and emphasize the important intersection of business and technology.
Proven ability to handle multiple products/work streams and demands efficiently.
Experience in leading a team of individuals with various levels of skills and experience in potentially high-stress and challenging situations.
Experienced with the data analytics ecosystem: data integration, data delivery, data preparation, data discovery, data processing, data storage, data science, and machine learning.
Aptitude to learn techniques and technologies regarding mathematical modeling, artificial intelligence, and machine learning.
Experience in DevOps, ADO, and GitHub toolchain and technologies.
Demonstrated initiative, flexibility, and ability to adapt to changing priorities and work environment.
Leads, influences, and upholds technology standards to ensure resiliency goals are met and continuously improved upon.
Basic financial skills.

Experience
9-12 yrs