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Mô tả công việc: Key Responsibilities Data Engineering Pipelines Build and maintain data pipelines for Amazon SP-API, Advertising API, and other e-commerce platforms. Collect and process product reviews, sales,…
Build and scale backend services for AI-powered voice assistants and call-center platforms using Python, LLMs, STT/TTS, and real-time voice pipelines.
Build and integrate generative-AI features (LLMs, retrieval/grounding) into production systems, focusing on document processing, classification, and secure, reliable AI services.
Design and build LLM-powered multi-agent systems for digital banking using Google ADK and LangGraph, integrating RAG pipelines, tool calling, and robust orchestration for production deployment.
Build full-stack MERN apps with TypeScript, integrate RAG pipelines and LLM services, and deploy on AWS/GCP.
Design and solve complex, real-world data science problems in Python and SQL to train and improve generative AI models for diverse industries.
Lead a team building cloud-native data platforms and AI pipelines, owning product backlogs and driving scalable solutions for Generative AI, LLMs, and vector databases.
Builds and maintains distributed systems for GNSS interference monitoring and deploys RAG/LLM pipelines for space and government missions using .NET Core or TypeScript/Node.js and Angular/React.
Build and deploy Generative AI systems using LLMs, RAG pipelines, and cloud infrastructure; work with Python, LangChain/LangGraph, vector DBs, and SQL.
Build and ship AI-powered marketing and sales platforms using Next.js, Node.js, and AI agents with LangChain/CrewAI, deploying on AWS/GCP via Terraform and GitHub Actions.
Builds backend services and cloud-native AI pipelines on AWS, integrating LLM APIs, RAG workflows, and agentic AI tools like GitHub Copilot.
Builds Flask web apps and Plotly Dash dashboards for banking analytics, integrates local LLMs and RAG pipelines, and automates risk/compliance workflows.
Build and deploy generative AI apps using Python and LangChain, focusing on RAG systems, LLM orchestration, and vector databases.
Build and maintain AI systems, automation, and internal web apps using React/Next.js, Python, and Supabase/PostgreSQL; troubleshoot integrations and deployments.
Build and maintain a universal data platform that integrates enterprise data sources into automated pipelines, ensuring high-quality data for AI agents, LLMs, and RAG workflows using Python, SQL, and GCP services.
Design and own the full production lifecycle of sovereign AI systems for international governments, ensuring reliability, security, and real-time observability of LLM-based applications.
Build and maintain high-performance data pipelines that bridge operational technology (OT) systems like SCADA and IoT sensors with cloud analytics in the oil and gas sector, using Azure, Python, and Spark.
Design and build enterprise-grade AI systems using RAG, agentic workflows, and cloud platforms for HR and finance domains.
Build and improve AI-powered business solutions, cloud platforms, and automation tools using full-stack web development, LLMs, and secure enterprise systems.
Lead a hybrid role managing data engineering teams and client projects, designing Azure-based cloud data platforms and GenAI-ready data architectures for banking, insurance, and retail clients.
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