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About the Role We are seeking a passionate AI Data Architect to design and build the data foundation that makes AI work well across Kuok Group —specifically, the hybrid vector and knowledge graph layer (the enterprise…
Lead the design and deployment of GenAI solutions for insurance, including RAG pipelines, vector databases, and LLM fine-tuning on AWS to deliver context-aware AI capabilities.
Build and deploy AI agents and GenAI solutions using Azure AI Foundry, OpenAI, and LangChain, focusing on RAG pipelines, copilots, and agentic workflows.
Designs and builds the hybrid vector and knowledge graph layer that powers RAG across Kuok Group, including embedding pipelines, retrieval patterns, and data governance for AI systems.
Designs and builds AI/ML models and agentic systems to automate workflows, enhance client engagement, and drive decision-making across retail, marketing, and operations using Python, LLMs, and cloud platforms.
Backend Engineer building scalable AI orchestration frameworks, RAG systems, and cloud-native AI services using Python, PostgreSQL, and vector databases to power enterprise-grade generative AI applications.
Design and manage document ingestion pipelines using OCR, LLMs, and multimodal AI to extract and index content for semantic search and analytics.
Build and deploy AI-powered web apps and APIs for a digital asset platform, integrating LLMs, RAG, and agentic frameworks with Java Spring Boot, Kubernetes, and AWS.
Build and deploy scalable AI systems using Python, LLMs, and GenAI to transform documents into knowledge graphs and automate workflows for industrial and automotive clients.
Build and deploy scalable AI systems using LLMs and GenAI, transforming documents into knowledge graphs and automating code analysis with Python and FastAPI.
Build next-gen AI systems using LangGraph and GraphRAG to enable natural-language queries and insights from distributed data, with Python and AWS.
Build and optimize graph-based knowledge structures using Neo4j to power an AI-driven retrieval system for a live product.
Build and deploy deep-learning NLP models, fine-tune LLMs, and implement RAG and agentic AI systems while maintaining MLOps pipelines.
Builds and deploys AI-powered applications using LLMs, RAG, and agentic AI; integrates with cloud services and vector databases.
Build production-ready enterprise AI apps using LLMs, RAG, and AI agents with Python, FastAPI, and cloud platforms to automate workflows and unlock business knowledge.
Design and build enterprise data pipelines using Microsoft Fabric, Synapse, and Azure Data Factory to power analytics and AI workloads for an edtech company.
Build AI agents and integrations that connect DevRev’s platform with customers’ tools using TypeScript, Python, and APIs; deploy serverless functions and optimize RAG pipelines for real-time workflow automation.
Designs and builds scalable cloud data pipelines, warehouses, and analytics platforms using Python, SQL, Spark, and cloud tools like BigQuery and Snowflake, with optional Gen AI integration.
Designs and builds enterprise data pipelines using Microsoft Fabric, Synapse, and Azure Data Factory to power analytics and AI workloads.
Builds backend services and APIs in Python/TypeScript that orchestrate LLMs, vector databases, and agentic workflows for an AI-driven infrastructure automation platform.
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