{"id":1249748,"url":"https://alion.io/job/mondee-artificial-intelligence-architect","title":"Artificial Intelligence Architect","company":{"id":3806432,"name":"Mondee","domain":"mondee.com","url":"https://alion.io/company/mondee","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":30000,"max_usd":71000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":11},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Context Engineering","optional":false},{"name":"CrewAI","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"Milvus","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"Vertex AI","optional":false},{"name":"Weaviate","optional":false},{"name":"Fine-tuning","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"LoRA","optional":true},{"name":"MLFlow","optional":true},{"name":"PEFT","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-08-13T10:56:28Z","employer_posted_date":null,"last_verified_at":"2026-08-13T10:56:28Z","board_verified":false,"closed_at":null,"days_open":49,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":49},"description":"Job Title : AI Architect\n\nFounder & CEO's Office | Hyderabad (On-site) | Full-time\n\nAbout Tabhi (The Parent Company of Mondee) :\n\nTabhi 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.\n\nThe Tabhi Group of Companies :\n\n- 23 Companies - 3 AI Platforms - One Vision\n\n- Mondee (B2B) The Agentic AI Travel Marketplace\n\n- Miraee (B2E) The Next-Gen Employee Travel Platform\n\n- Abhee (B2C) The Hyperlocal Experiential Marketplace\n\nOur Scale :\n\n- 65K+ Global Customers\n\n- 500+ Airline Partners\n\n- 2M+ Hotels & Vacation Rentals\n\n- 50M Shopper Searches Per Day\n\n- 125M+ Consumers Access\n\nThe Opportunity :\n\nWe 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.\n\nThis 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.\n\nKey Responsibilities :\n\n- Design and build production-ready agentic AI systems, owning them from architecture through deployment, monitoring, and iteration.\n\n- Define reference architectures, technology selections, and integration patterns for AI systems across the three platforms.\n\n- Architect scalable AI infrastructure and intelligent workflows, including multi-agent orchestration and human-in-the-loop processes.\n\n- Build and maintain RAG pipelines, LLM integrations, and evaluation harnesses in production codebases.\n\n- Establish and enforce standards for responsible AI - guardrails, AI governance, data security, and model evaluation.\n\n- Own production reliability across the stack - agent failures, retrieval quality degradation, latency, and cost regressions.\n\n- Collaborate with product and engineering teams to translate complex business problems into working systems.\n\n- Shape the technical direction of AI across the organization, working directly with leadership.\n\nRequired Qualifications :\n\n- Experience : 7-10 years in software/AI engineering, including 3-5 years of hands-on experience delivering production machine learning or generative AI systems.\n\n- Programming : strong, current Python with a record of owning production code; solid software-engineering fundamentals including API design and distributed systems.\n\n- 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.\n\n- RAG and retrieval : production experience designing RAG architectures, embeddings, and vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus).\n\n- Prompt and context engineering : demonstrated ability to design prompts, context strategies, and evaluation methods that perform reliably at production scale.\n\n- 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.\n\n- MLOps/LLMOps : CI/CD for models and prompts, containerization with Docker/Kubernetes, observability/monitoring, and cost-performance optimization in production.\n\n- Responsible AI : working knowledge of AI governance, guardrails, security, and data-quality standards.\n\n- Communication : demonstrated ability to lead technical design reviews with engineers and present architecture decisions and trade-offs to executive stakeholders.\n\n- Education : Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience; Master's degree preferred.\n\nPreferred Qualifications :\n\n- Experience with agent reasoning patterns such as ReAct, Plan-and-Execute, Reflection, and Tree-of-Thought.\n\n- Model fine-tuning experience (e.g., LoRA/PEFT) and familiarity with knowledge graphs.\n\n- Experience with ML frameworks (PyTorch, TensorFlow) and experiment/model management (MLflow).\n\n- Cloud architecture certification (Azure Solutions Architect Expert, AWS Solutions Architect Professional, or equivalent).\n\n- Experience building consumer- or marketplace-scale systems in travel, e-commerce, or similar high-volume domains.\nSkills\nArtificial Intelligence, Technical Architect, Generative AI, Gen AI Strategy, AI Governance, AI Project Management, AI Strategy, Agentic AI, Machine Learning, Large Language Model","description_format":"text","description_chars":4676,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-25T18:00:00Z"}],"liveness":{"score":10,"band":"cold","label":"Long shot","p_open":0.4,"p_active":0.543,"p_room":0.45,"age_days":48,"expected_fill_days":30,"reasons":["seen:48","win:tail"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/mondee-artificial-intelligence-architect","json_url":"https://alion.io/job/mondee-artificial-intelligence-architect.json","meta":{"generated_at":"2026-10-02T02:28:45Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3299,"day_limit":5000,"remaining_today":1701,"minute_limit":60,"resets_at":"2026-10-03T00:00:00Z"}}}