AI infrastructure and RAG systems for enterprise chatbots and multi-agent workflows
Ant-Tech is a small engineering team building AI-native applications with a modern stack spanning Solidity, Rust, TypeScript, and Python, layered with ML infrastructure (PyTorch, TensorFlow, FAISS, Milvus, Weavert, Chroma, MLflow, Weights & Biases). The project list—chatbot systems, advanced RAG workflows, multi-agent systems, and Web3 talent sourcing—reveals a pivot from traditional web/mobile consulting toward production AI systems. Hiring is accelerating across junior and mid-level engineers in Southeast Asia, suggesting an attempt to scale inference and RAG optimization while keeping costs down.
Ant-Tech, founded in 2016 and headquartered in Lyon, France, began as a consulting and custom software development shop serving small to large companies across Europe, North America, and Asia. The company has shifted its focus toward AI infrastructure and intelligent agent systems. Core competencies now include chatbot design, retrieval-augmented generation (RAG) workflows, and multi-agent orchestration. The team operates at 11–50 employees and is actively hiring engineers in the Philippines and Vietnam, indicating a remote-first scaling model for infrastructure and development work.
Solidity, Rust, TypeScript, React, Python, PyTorch, TensorFlow, FAISS, Milvus, Chroma, Weaviate, MLflow, Weights & Biases, Docker, Kubernetes, and AWS/GCP/Azure.
Chatbot systems, advanced RAG workflows, multi-agent workflows, and candidate sourcing for Web3 roles. Pain points include scaling AI/LLM production and optimizing inference cost.
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