AI Engineer (Full-time)

Indonesia Remote March 15, 2026

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