AI Solutions Architect: Travel, Transportation & Hospitality

Location: London, UK DataArt’s Travel, Transportation & Hospitality Practice is looking for a client-facing professional. The role connects advanced AI tools to real business impact and involves working with client account teams and the AI + Data Lab across 50+ active travel accounts to find high-value use cases, prototype fast, validate with stakeholders, and drive adoption from C-suite to delivery teams. The role covers the journey from prototype to production. You will define how solution quality is measured once a solution is live and design for the controls enterprise clients operate under. Lead ideation and scoping of AI and ML proofs of concept with client account leaders Prototype AI features such as copilots, NLP services, and recommender systems Own the full lifecycle from internal demo and stakeholder validation to client presentation and the path to production Direct internal teams to execute with clarity, velocity, and alignment Build GenAI applications using RAG variations, agentic and hybrid models, cloud AI services, LLM APIs, vector search, and agentic SDKs Integrate AI solutions with Snowflake and Databricks Define how solution quality is measured in production through evaluation sets, accuracy checks, groundedness checks, drift detection, human in the loop checkpoints, and audit records Define reusable AI building blocks and travel specific agent scaffolds for internal delivery practices Shape internal best practice for GenAI across delivery Embed AI into client products and operations for personalization, crew operations, service automation, disruption handling, post booking servicing, reconciliation, and refunds Run workshops with client teams and business leaders Act as a translator and evangelist for responsible AI adoption and ROI Hands on experience with AI services from at least one major cloud such as Azure, AWS, or GCP Experience designing and implementing RAG based applications Experience taking AI solutions beyond pilot into production Experience validating AI solution performance before go live and monitoring it after release Practical understanding of AI evaluation including defining workflow correctness, building test sets, and measuring accuracy and groundedness Strong background with Snowflake and or Databricks for data engineering and AI pipelines Proven success leading client facing proofs of concept or MVPs from inception to delivery at Director level or above Ability to turn ambiguous business goals into scoped, testable, and scalable initiatives Fluency in open source versus commercial model tradeoffs and cost efficient architecture Prior exposure to the travel, transportation, or hospitality sector Experience with vector databases Experience with context engineering Experience with orchestration frameworks such as LangChain or Semantic Kernel Familiarity with fine tuning and understanding of when it is worth the effort Experience with agentic loop engineering Experience with AI observability or evaluation tooling Awareness of responsible AI practices including fairness, explainability, and usage boundaries