ExaTech Inc

AI Engineer with Cursor AI

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Engineer with a contract length of "unknown," offering a pay rate of "unknown." It requires hybrid work in Austin, TX, and expertise in Python, agent development, RAG architectures, and Cursor AI.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 4, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Austin, Texas Metropolitan Area
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🧠 - Skills detailed
#Scala #Programming #Python #AI (Artificial Intelligence) #Debugging #Langchain
Role description
AI Engineer Location: Hybrid (Austin TX) Job Summary We are seeking a highly skilled AI Engineer with hands-on experience in agent development, Retrieval-Augmented Generation (RAG), agentic workflows, and platforms such as Cursor AI. The ideal candidate will have a strong developer mindset and expertise in integrating APIs and building intelligent systems that can reason, act, and interact across tools and data sources. Key Responsibilities • Design, develop, and optimize AI agents capable of reasoning, decision-making, and tool usage • Implement and fine-tune RAG pipelines for contextual knowledge integration • Develop, integrate, and manage agentic workflows across APIs, vector stores, and third-party tools • Leverage Cursor AI and similar platforms to prototype and deploy agent-based applications • Collaborate with product teams to implement AI-driven features with seamless developer experience • Build scalable APIs for model access, integration, and service orchestration • Stay updated with the latest in LLMs, agent orchestration frameworks, and AI tooling Required Skills & Qualifications • Strong programming skills in Python or equivalent (Go/Node.js is a plus) • Experience in developing autonomous agents and agentic workflows using frameworks like LangChain, AutoGen, or similar • Hands-on with Cursor AI for development, debugging, and agent orchestration • Experience building and consuming RESTful APIs • Proficiency in RAG architectures, including vector stores (e.g., FAISS, Pinecone, Weaviate), embedding models, and retrieval tuning • Experience with prompt engineering, tool calling, and multi-agent collaboration setups • Solid understanding of LLMs, their fine-tuning strategies, and evaluation frameworks