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Build and scale data pipelines, crawlers, and semantic search systems using Golang/Node.js, PostgreSQL, and vector databases to power AI-driven financial analytics and RAG integrations.
Build and optimize open-source AI models (VinaSmol) and RAG systems, focusing on Vietnamese language support and hallucination detection using Python, React, and ML/NLP techniques.
Build and maintain LLM servers (Llama, Mistral, GPT API) and deploy AI agents that automate tasks like reminders, reports, and paperwork using vector databases and RAG pipelines.
Build and deploy AI models using Python, PyTorch/TensorFlow, and frameworks like LangChain and LlamaIndex; package models for production and collaborate on R&D.
Build and improve natural-language applications using Python, ML algorithms, and neural networks; analyze data and customer needs to deliver AI-driven solutions.
Build and scale backend services for AI-powered voice assistants and call-center platforms using Python, LLMs, STT/TTS, and real-time voice pipelines.
Lead a backend and data engineering team to build a zero-hallucination RAG platform, designing scalable data pipelines, APIs, and distributed workflows using Python, Apache Beam, FastAPI, and Temporal.
Design and build enterprise-grade conversational AI systems using LLMs, RAG, and prompt engineering, ensuring security and compliance.
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.
Design and build generative AI solutions using LLMs, agentic systems, and RAG pipelines, optimizing models and managing unstructured data in production.
Build full-stack MERN apps with TypeScript, integrate RAG pipelines and LLM services, and deploy on AWS/GCP.
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 deploys generative-AI solutions (RAG, prompt engineering, AI guardrails) using LangChain, LangGraph, and PyTorch for enterprise clients in Milan.
Designs and builds RAG/LLM components and evaluates response quality for an AI-focused product company.
Builds and deploys generative-AI and RAG pipelines on Azure OpenAI to automate insurance workflows, working with Python, LLM models, and Microsoft Fabric.
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 Flask web apps and Plotly Dash dashboards for banking analytics, integrates local LLMs and RAG pipelines, and automates risk/compliance workflows.
Builds Flask-based web apps and data dashboards with Plotly Dash, integrating LLMs and RAG for intelligent, AI-driven solutions.
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.
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