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.