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Design and deliver AI architectures for clients, focusing on RAG pipelines, agentic workflows, and LLM integrations using Python, cloud AI platforms, and vector databases.
Build and operate an internal AI platform for LLM and agentic applications, including retrieval, deployment, and monitoring, using Python, FastAPI, and cloud services.
Build and deploy AI-powered NLP/LLM features for a SaaS quality-management platform used by global contact centers, working with Python, Hugging Face, and AWS.
Build and deploy LLM-powered automation agents for pharma workflows using Python/JavaScript, PostgreSQL, vector DBs, and n8n on an NVIDIA DGX Spark AI sandbox.
Builds and deploys production-grade AI/data pipelines: LLM apps (RAG, agents), graph/ETL workflows, and cloud-native data platforms using Python, FastAPI, Airflow, Snowflake, and vector stores.
Build and deploy LLM-based AI systems for government services using RAG, fine-tuning, and prompt engineering with Python, LangChain, and cloud ML services.
Design and scale RAG pipelines that turn IT logs and docs into vector embeddings, maintain high-performance vector databases, and build semantic layers for AI agents.
Build and operate an internal AI platform for a fintech company, designing retrieval layers, agent runtimes, and deployment pipelines using Python, FastAPI, and cloud services.
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…
Build and deploy AI-powered applications using LLMs, vector databases, and AI orchestration frameworks like LangChain or Semantic Kernel.
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.
Design and deliver AI-ready data platforms, ML pipelines, and GenAI-specific data flows for clients using cloud ecosystems like AWS, Azure, and GCP.
Build AI-ready data pipelines and knowledge systems for an investment firm’s agentic AI, integrating structured financial data, unstructured research, and real-time feeds into vector stores, graph databases, and retrieval pipelines.
Design and build AI-ready data platforms and ML pipelines for analytics, GenAI, and RAG systems on AWS/Azure/GCP, ensuring production-grade delivery and MLOps practices.
Build full-stack web apps and integrate AI features using modern stacks (React, Node.js/Python/.NET, SQL/NoSQL) while leveraging AI coding assistants daily.
Build full-stack web apps and integrate AI features using modern stacks, AI coding assistants, and LLM APIs to deliver enterprise solutions.
Build production-grade AI systems like copilots, RAG, and agents using LLMs and vector databases, deploying them in enterprise environments.
Build and deploy production-grade AI systems, including LLM-based applications, RAG pipelines, and agentic workflows, across a large Saudi conglomerate's diverse business units.
Build and maintain the data pipelines and retrieval layer that power Mirai’s Generative AI products on AWS, including vector stores, embeddings, and governed datasets.
Lead the architecture and strategy of JLL’s enterprise data platform, consolidating global systems into a unified, scalable data layer to power AI-driven insights and analytics for commercial real estate.
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