AI Consultant

The AI Consultant will play a critical role in driving artificial intelligence adoption across the airline by designing and delivering intelligent, scalable AI solutions that enhance decision-making, optimize business performance, and automate processes. This role combines strategic advisory responsibilities with hands-on delivery, working closely with business and IT stakeholders to translate challenges into high-impact AI, machine learning, and generative AI use cases that unlock new digital capabilities. Key Responsibilities: - Partner with IT and business leadership to define and refine the enterprise AI strategy aligned with organizational objectives. - Identify high-value AI use cases that improve efficiency, performance, and customer experience. - Lead end-to-end design, development, and deployment of AI, machine learning, and generative AI solutions. - Translate business requirements into scalable AI architectures and models. - Ensure availability, quality, and reliability of data required for AI initiatives. - Oversee model lifecycle management, including testing, monitoring, retraining, and continuous improvement. - Deliver predictive and prescriptive analytics to support strategic and operational decision-making. - Apply advanced analytical techniques to uncover trends, risks, and optimization opportunities. - Work closely with business units to co-design AI-enabled solutions that address real operational challenges. - Act as a bridge between technical teams and business stakeholders. - Assess emerging AI technologies, platforms, and tools. - Recommend and support adoption of best-fit AI solutions and frameworks. - Lead AI workstreams, managing timelines, dependencies, and stakeholder expectations. - Communicate progress, risks, and outcomes effectively to senior stakeholders. - Ensure AI solutions comply with governance, data privacy, and regulatory requirements. - Promote responsible and ethical AI practices across the organization. - Support change management activities related to AI adoption. - Train end users and stakeholders to ensure effective utilization of AI solutions. Requirements: Education - Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, or a related field. Experience - Proven experience delivering enterprise-scale AI, machine learning, or advanced analytics solutions. - Strong hands-on background in machine learning, generative AI, natural language processing (NLP), and advanced analytics. - Experience working in cross-functional environments with both technical and non-technical stakeholders. Certifications (Preferred) - AI / Machine Learning certifications. - Cloud platform certifications (e.g., AWS, Azure, GCP). Competencies - Strong analytical and problem-solving skills. - Ability to translate complex technical concepts into business-friendly insights. - Excellent stakeholder management and communication skills. - Structured, delivery-focused mindset with a strong sense of ownership.

Partner with IT and business leadership to define and refine the enterprise AI strategy aligned with organizational objectives. Identify high-value AI use cases that improve efficiency, performance, and customer experience. Lead end-to-end design, development, and deployment of AI, machine learning, and generative AI solutions. Translate business requirements into scalable AI architectures and models. Ensure availability, quality, and reliability of data required for AI initiatives. Oversee model lifecycle management, including testing, monitoring, retraining, and continuous improvement. Deliver predictive and prescriptive analytics to support strategic and operational decision-making. Apply advanced analytical techniques to uncover trends, risks, and optimization opportunities. Work closely with business units to co-design AI-enabled solutions that address real operational challenges. Act as a bridge between technical teams and business stakeholders. Assess emerging AI technologies, platforms, and tools. Recommend and support adoption of best-fit AI solutions and frameworks. Lead AI workstreams, managing timelines, dependencies, and stakeholder expectations. Communicate progress, risks, and outcomes effectively to senior stakeholders. Ensure AI solutions comply with governance, data privacy, and regulatory requirements. Promote responsible and ethical AI practices across the organization. Support change management activities related to AI adoption. Train end users and stakeholders to ensure effective utilization of AI solutions.