AI Engineer (Full-time)

Kata.ai is an Indonesian Conversational Artificial Intelligence company seeking an AI Engineer to design, build, and deploy production-grade AI systems for enterprise clients. The ideal candidate will have a strong background in AI/ML engineering and experience with LLM-powered conversational agents, RAG pipelines, and NLP workflows.

Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Computational Linguistics, or related field
• Master's degree in AI/ML is a plus
• Relevant certifications (GCP AI/ML, DeepLearning.AI, etc.) are advantageous
• 1–2 years of professional experience in AI/ML engineering or software development with a strong AI focus
• Hands-on experience building or integrating LLM-powered applications using OpenAI, Anthropic Claude, Google Gemini, or equivalent
• Practical exposure to conversational AI or chatbot development — prompt engineering, intent handling, or dialogue flow design
• Familiarity with RAG pipeline concepts — document ingestion, embedding, vector search, and retrieval
• Experience with Python and at least one AI orchestration framework (LangChain, LlamaIndex, or similar)
• Exposure to cloud platforms (GCP or Azure) for deploying AI/ML workloads
• 3–5 years of experience in AI/ML or software engineering, with at least 2 years focused on production-grade LLM or GenAI systems
• Proven experience designing and deploying RAG pipelines in production — including chunking strategies, embedding models, vector databases (Qdrant, Pinecone, Weaviate, or pgvector), and retrieval optimization
• Hands-on experience building conversational AI systems for enterprise clients — chatbot, virtual assistant, or AI agent products in regulated industries
• Demonstrated experience with Voice AI integrations — STT (Deepgram, Whisper, Google Speech-to-Text) and/or TTS (ElevenLabs, Google TTS) in a production environment, ideally with LiveKit Agents SDK or equivalent
• Experience implementing AI evaluation frameworks (RAGAS, DeepEval, or custom eval pipelines) to measure and improve model quality
• Experience with AI observability tooling — LangSmith, Langfuse, or custom LLM call tracing in production

Benefits

• Flexible working hours
• Learning experience in Conversational AI Industry

Originally posted on Himalayas