Artificial Intelligence Engineer

AI Product Engineer

About the role

We are building an AI-native travel platform for our travel advisors and partners hence we are looking for a highly entrepreneurial AI product builder with a Computer Science background from a premier engineering institute, who can take end-to-end ownership of the product's technical foundation and work directly with the business.

This is not a research-only role and not a narrow backend engineering role. The person must be able to convert an ambiguous business problem into a working product.

Key responsibilities

Product and AI architecture

• Design the end-to-end architecture of the AI-native platform.
• Translate customer and advisor workflows into AI-driven product experiences.
• Build systems that understand intent, preferences, and traveller context.
• Design agentic flows that can search, reason, compare, recommend, trigger actions and determine where AI should automate, assist or hand off to humans.
• Build rapid prototypes and convert successful experiments into production systems.
• Work closely with design and product teams to develop conversational and workflow-based interfaces.
• Balance speed, quality and scalability during the zero-to-one phase.
• Build evaluation frameworks for relevance, hallucination and consistency.
• Implement guardrails for pricing, availability, policy and factual accuracy.
• Monitor AI output quality and continuously improve recommendations.

Travel supply and transaction integration

• Integrate various supply APIs or build system to consume it.
• Support various workflows and exception-handling mechanisms.
• Design integration layers that are resilient to inconsistent partner data.

Engineering leadership

• Make early technology-stack and architecture decisions.
• Establish practical engineering standards without introducing unnecessary bureaucracy.
• Work closely with product, design, supply and operations teams.
• Own technical delivery and communicate trade-offs clearly to leadership.

Must-have capabilities

• Strong full stack engineering skills
• Hands-on experience with LLM-based applications
• Experience with RAG, embeddings, vector search and tool calling
• Understanding of agentic workflows and orchestration
• Experience building APIs and integrating external platforms
• Strong database and data-modelling knowledge
• Experience with cloud platforms and production deployment
• Knowledge of AI evaluation, observability and guardrails
• Ability to build both prototypes and scalable production systems
• Strong product intuition and customer-oriented thinking

Desirable capabilities

• Recommendation systems and ranking
• Search and information retrieval
• Knowledge graphs
• Marketplace or booking-engine experience
• Travel inventory or supplier integrations
• Multi-tenant or white-label platform architecture
• Conversational interfaces
• Personalisation systems
• Payments and transaction workflows

Behavioural qualities

• Highly entrepreneurial: Comfortable working without detailed specifications and able to create structure from ambiguity.
• Hands-on: Willing to write code, test ideas, review architecture and solve immediate product problems.
• Fast but thoughtful: Able to move quickly without creating avoidable technical debt.
• Resourceful: Looks for practical solutions rather than waiting for perfect data, perfect tools or a large team.
• Product-minded: Understands that the goal is not only to demonstrate AI capability, but to solve a customer and business problem.
• Commercially aware: Can connect technical choices to conversion, productivity, revenue, cost and customer experience.
• Comfortable challenging assumptions: Should respectfully debate product choices and propose better alternatives.
• Agile and adaptable: Able to change direction quickly based on customer feedback, technical learning or business priorities.
• High ownership: Does not say, 'This belongs to product,' 'This belongs to data,' or 'This belongs to operations.' Takes responsibility for getting the outcome delivered.

Skills Required
production deployment