🚀 AI Engineer | AI Developer | GenAI & LLM Systems AI should do more than generate text — it sho...🚀 AI Engineer | AI Developer | GenAI & LLM Systems AI should do more than generate text — it sho...
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🚀 AI Engineer | AI Developer | GenAI & LLM Systems
AI should do more than generate text — it should solve real business problems.
I build production-ready AI systems that combine LLMs, RAG, AI Agents, automation, and cloud infrastructure to turn complex workflows into intelligent products.
🔹 What I build → AI Agents & multi-agent systems → RAG / knowledge assistants → LLM-powered applications → Document & data intelligence → AI automation workflows → NLP & Generative AI solutions → Cloud-based AI platforms
🔹 Tech stack Python • PyTorch • LangChain • LlamaIndex • OpenAI • Azure AI • GCP • AWS • RAG • Vector Databases • Docker • Kubernetes • React • TypeScript
I focus on the full lifecycle — from AI architecture and prototyping to deployment and production optimization.
Looking for someone who can take an AI idea from “this could be useful” → “this is running in production”?
📩 Let’s build it.
#AI #ArtificialIntelligence #AIAgents #GenerativeAI #LLM #RAG #MachineLearning #AIEngineer #Python #AzureAI #GCP #Freelance
Nugraha's avatar
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@Norbert Łaszanowski Covering architecture through production optimization is a useful distinction. How do you typically evaluate RAG quality before deploying on Azure or GCP?
Norbert's avatar
I typically evaluate RAG using retrieval precision/recall, context relevance, groundedness, hallucination rates, and end-to-end latency, combining automated evaluation with real-world test cases before deploying to Azure or GCP.
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The network for creativity
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Creatives on Contra have earned over $150M and we are just getting started