Role Summary

Build and ship AI-powered features and automation workflows as part of the offshore AI engineering pod, extending the organization's LLM-based sales, CRM, and operations tooling under the direction of the Dubai-based AI Engineering team.

Key Responsibilities

- Develop LLM-powered features, chat assistants, and automation workflows

- Implement RAG pipelines: ingestion, chunking, embeddings, retrieval, citation

- Write and iterate on prompts, tool definitions, and agent workflows

- Integrate AI features with Salesforce, ERP, and platform APIs

- Build evaluation scripts and monitor model output quality and cost

- Collaborate closely with the Dubai AI Engineering team across time zones

Tech Stack

- Languages: Python and/or JavaScript/TypeScript

- LLM APIs: Anthropic Claude, OpenAI, Azure OpenAI

- Frameworks: LangChain, LlamaIndex, Anthropic Agent SDK

- Vector stores: pgvector, Pinecone, Azure AI Search

- Backend: FastAPI / Node.js, REST & GraphQL

- Cloud: Azure, Docker; CI/CD via GitHub Actions/Azure DevOps

Cutting-Edge AI Skills

- Prompt engineering, structured outputs, and function/tool calling

- RAG pipeline construction and retrieval tuning

- Multi-step agent design and Model Context Protocol (MCP) tool integration

- Building evaluation sets and monitoring for hallucination/quality drift

Business Domain Exposure





- The organization is a large-scale master real estate developer delivering mixed-use residential, commercial, and hospitality communities across multiple master-planned developments, alongside affiliated retail, wellness/fitness, food & beverage, hospitality, education, and property-management operating brands.

- Supporting AI features for sales/CRM automation and buyer-facing chat/search

- Working with property, pricing, and inventory data from the organization's master-community projects

- Coordinating with Dubai AI Engineering on grounding AI outputs against Salesforce/ERP data

Must-Have Requirements

- Proficiency in Python and/or JavaScript/TypeScript

- Practical experience building with LLM APIs and prompt engineering

- Understanding of vector databases and embedding-based retrieval

- Comfortable working with REST/GraphQL APIs and cloud services

- Robust async communication skills for distributed teams

Nice to Have

- Experience with agent frameworks (LangChain, LlamaIndex, or similar)

- Exposure to CI/CD and containerized deployments

- Interest in enterprise SaaS/real-estate integrations

Pay: Up to ₹130,000.00 per month

Application Question(s)

- 4–6 years data science engineering, with applied AI/LLM project experience?

Education

- Master's (Required)

Experience

- AI/LLM project : 6 years (Required)

- Data science: 4 years (Required)

Work Location: In person

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