Job
Description
You will be playing a key role in designing and implementing enterprise-grade GenAI architectures across various aspects such as discovery, search, booking, and service automation. Your responsibilities will include building cloud-native AI applications on AWS, Azure, or GCP, utilizing platform-native services like Bedrock, Azure OpenAI, and Vertex AI. You will also be developing and orchestrating AI workflows using LLMs, RAG, embeddings, and agent frameworks such as LangChain and LlamaIndex. Additionally, you will architect autonomous AI agents for tasks like itinerary planning, fare optimization, customer service, and supplier interactions, ensuring a robust enterprise architecture that covers scalability, performance, observability, and governance. Collaboration with product, engineering, and data teams will be essential to embed AI across the customer and operational lifecycle. Key Responsibilities: - Design and implement enterprise-grade GenAI architectures across discovery, search, booking, and service automation. - Build cloud-native AI applications on AWS, Azure, or GCP, leveraging platform-native services (e.g., Bedrock, Azure OpenAI, Vertex AI). - Develop and orchestrate AI workflows using LLMs, RAG, embeddings, and agent frameworks (LangChain, LlamaIndex, etc.). - Architect autonomous AI agents for itinerary planning, fare optimization, customer service, and supplier interactions. - Ensure robust enterprise architecture, covering scalability, performance, observability, and governance. - Collaborate with product, engineering, and data teams to embed AI across the customer and operational lifecycle. Qualifications Required: - Expertise in designing and deploying LLM-based solutions in production environments. - Deep experience in cloud-native development on AWS, Azure, or GCP. - Strong background in enterprise architecture, APIs, microservices, and containerized deployments. - Proficiency in RAG, vector DBs (e.g., Pinecone, Weaviate), embeddings, and AI orchestration. - Programming skills in Java, Typescript, Python. In addition to the above, it is good to have prior experience in Airlines, Hospitality, or OTA platforms, familiarity with agentic AI frameworks like LangGraph, Langfuse, Autogen, and exposure to multimodal AI encompassing text, image, speech, maps, and geo-personalization. Please note that the job offers an opportunity to work on building the core AI engine for a next-gen travel platform, the chance to work at scale with deep AI and cloud integration, competitive compensation, and a flexible work environment.,
