AI ML Engineer

· Work with business and technology stakeholders to understand and translate opportunities and requirements into well-defined AI problems.

· Develop production-grade AI services, APIs, microservices, and integrations using sound software engineering principles.

· Build solutions using appropriate techniques such as generative AI, natural language processing, retrieval, classification, prediction, recommendation, or optimisation.

· Develop AI application workflows that may include prompting, structured outputs, tool use, agent orchestration, search, retrieval-augmented generation, and conversational context.

· Create and maintain data ingestion, preparation, indexing, retrieval, and model-serving pipelines where required.

· Define evaluation approaches using representative datasets, automated tests, quality metrics, human review, and business outcomes.

· Deploy, monitor, and support AI solutions in cloud environments, balancing quality, reliability, latency, scalability, and cost.

· Investigate production issues using logs, traces, metrics, evaluation results, and user feedback, and drive improvements through the full product lifecycle.

· Integrate AI capabilities with enterprise systems, external services, and existing technology platforms.

· Contribute to technical documentation, testing, CI/CD practices, and reusable engineering patterns.

· Clearly communicate assumptions, limitations, risks, uncertainty, and technical trade-offs to technical and non-technical audiences.

· Develop an understanding of the airline and travel domain and how technology supports customers, colleagues, and operations.