Artificial Intelligence Architect

AI Architect

Founder & CEO's Office | Hyderabad (On-site) | Full-time

About Tabhi (The Parent Company of Mondee)

Tabhi is a $4B AI-native travel company and the world's largest AI-first travel platform, revolutionizing travel, tourism, and experiential services through three integrated, AI-powered verticals.

The Tabhi Group of Companies

23 Companies • 3 AI Platforms • One Vision

• Mondee (B2B) The Agentic AI Travel Marketplace
• Miraee (B2E) The Next-Gen Employee Travel Platform
• Abhee (B2C) The Hyperlocal Experiential Marketplace

Our Scale

• 65K+ Global Customers
• 500+ Airline Partners
• 2M+ Hotels & Vacation Rentals
• 50M Shopper Searches Per Day
• 125M+ Consumers Access

The Opportunity

We are seeking AI Architect(s) to join the Founder & CEO's Office to design and deliver the next generation of production-grade AI systems across the Tabhi Group.

This is a hands-on architecture role. The AI Architect is accountable both for the system-level view architecture, scalability, governance, and business impact and for the engineering detail required to complete each build cycle and deliver the product: retrieval design, evaluation, deployment, monitoring, and cost control. Architecture at Tabhi is measured by shipped, operating software.

Key Responsibilities

• Design and build production-ready agentic AI systems, owning them from architecture through deployment, monitoring, and iteration.
• Define reference architectures, technology selections, and integration patterns for AI systems across the three platforms.
• Architect scalable AI infrastructure and intelligent workflows, including multi-agent orchestration and human-in-the-loop processes.
• Build and maintain RAG pipelines, LLM integrations, and evaluation harnesses in production codebases.
• Establish and enforce standards for responsible AI: guardrails, AI governance, data security, and model evaluation.
• Own production reliability across the stack — agent failures, retrieval quality degradation, latency, and cost regressions.
• Collaborate with product and engineering teams to translate complex business problems into working systems.
• Shape the technical direction of AI across the organization, working directly with leadership.

Required Qualifications

• Experience: 7–10 years in software/AI engineering, including 3–5 years of hands-on experience delivering production machine learning or generative AI systems.
• Programming: strong, current Python with a record of owning production code; solid software-engineering fundamentals including API design and distributed systems.
• Agentic AI and LLMs: hands-on experience with LLM-based and autonomous agent systems, including multi-agent frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGen.
• RAG and retrieval: production experience designing RAG architectures, embeddings, and vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus).
• Prompt and context engineering: demonstrated ability to design prompts, context strategies, and evaluation methods that perform reliably at production scale.
• Cloud AI platforms: deep experience with at least one major cloud AI stack — Azure OpenAI, AWS Bedrock/SageMaker, or Google Vertex AI — plus familiarity with data platforms such as Databricks or Snowflake.
• MLOps/LLMOps: CI/CD for models and prompts, containerization with Docker/Kubernetes, observability/monitoring, and cost-performance optimization in production.
• Responsible AI: working knowledge of AI governance, guardrails, security, and data-quality standards.
• Communication: demonstrated ability to lead technical design reviews with engineers and present architecture decisions and trade-offs to executive stakeholders.
• Education: Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience; Master's degree preferred.

Preferred Qualifications

• Experience with agent reasoning patterns such as ReAct, Plan-and-Execute, Reflection, and Tree-of-Thought.
• Model fine-tuning experience (e.g., LoRA/PEFT) and familiarity with knowledge graphs.
• Experience with ML frameworks (PyTorch, TensorFlow) and experiment/model management (MLflow).
• Cloud architecture certification (Azure Solutions Architect Expert, AWS Solutions Architect Professional, or equivalent).
• Experience building consumer- or marketplace-scale systems in travel, e-commerce, or similar high-volume domains.

Application Process

As part of the hiring process, candidates will complete one of two production-inspired AI architecture case studies.

The assessment evaluates engineering judgment, system design approach, and the ability to build production-ready AI solutions — both the architectural thinking and the execution detail. A working implementation, GitHub repository, and a short architecture walkthrough are required for successful consideration.

Role Details

Role

AI Architect

Team

Founder & CEO's Office

Experience

7–10 Years

Employment Type

Full-time

Location

Hyderabad (On-site)

If you have designed AI systems that operate at production scale and want to work directly with leadership on high-impact problems, we encourage you to apply.

Apply now and show us how you build.