Kata.ai

• Manage end-to-end monthly payroll operations • Ensure accurate, timely, and compliant HR administration • Provide reliable payroll support to employees • Operate smoothly the People & Culture function during coverage period

• Assure the quality of software or apps deployed is stable according to requirements • Work together with the team to define acceptance criteria • Write test cases, do smoke, regression, and integration tests regularly • Work together to enhance the software development phase • Act as 1st layer technical support for the support team

• Lead and operate the Technical Support function — managing client issue triage, BAU client requests, SLA performance, incident response, RCA quality, and continuous workflow improvement — for Kata's chatbot, voice AI, and Omnichannel platforms across a portfolio of enterprise clients in regulated industries. • Chair the weekly Incident Review forum to convert recurring incidents into structured action items for Engineering and Product, so that clients experience reliable 24/7 service continuity, fast and high-quality resolution, and so that operational insights flow back into Engineering and Product teams to systematically reduce recurring issues at the platform level.

• Run Kata.ai's Technical Support function end-to-end — managing client issue triage, BAU client requests, SLA performance, incident response, RCA quality, and continuous workflow improvement — across Kata's chatbot, voice AI, and Omnichannel platforms for a portfolio of enterprise clients in regulated industries. • Lead the weekly Incident Review forum to convert recurring incidents into structured action items for Engineering and Product, so that clients experience reliable, fast, and high-quality service resolution — and so that operational insights flow back into Engineering and Product to systematically reduce recurring issues at the platform level.

• Responsible for designing, building, implementing, and maintaining solutions and third-party integrations that work with Kata Platform for our partners • Building chat bots

• Responsible for configuring WhatsApp Business API, Kata CX, and Omnichannel accounts. • Resolving technical issues via email, tickets, WhatsApp, and SeaTalk. • Proactively monitoring system health and maintaining custom client reports. • Managing Kata CX credit top-ups and addressing client inquiries regarding chatbot functionality. • Investigating incidents through log analysis and creating Root Cause Analysis (RCA) documentation.

• Own and grow a portfolio of key enterprise clients • Build long-term partnerships and navigate complex sales cycles • Deliver real business impact across FMCG, Banking & Financial Services, Healthcare, and Pharmaceuticals • Work consultatively with VP and C-suite stakeholders • Translate AI-powered solutions into measurable business value • Become a trusted strategic partner to clients who rely on us to help them grow

• Design, build, and maintain scalable data pipelines, streaming infrastructure, and AI/ML data workflows that power data-driven products and enterprise AI solutions • Ensuring reliable, timely, and high-quality data is available across the organization • So that AI Engineers, Product teams, and enterprise clients can make accurate, insight-driven decisions and deliver intelligent customer experiences through Kata's AI and voice platforms

• Design, develop, and maintain performant, accessible, and visually accurate frontend applications for enterprise clients • Translating product requirements and UI/UX designs into high-quality user interfaces that support Kata's AI-powered customer experience, chatbot, and voice communication platforms • Ensuring enterprise clients and their end users have a seamless, reliable, and intuitive product experience

Company Description Kata.ai is an Indonesian Conversational Artificial Intelligence company with a focus on creating technology to enhance the understanding of human conversations, improving the way humans collaborate with machines. Kata.ai’s Natural Language Processing (NLP) technology powers MultiPurpose chatbots (virtual customer service / virtual friend) for major corporations in Indonesia across different kinds of industries such as Unilever (FMCG), Telkomsel (Telco), Bank BRI (Financial Services), and Alfamart (Retail). The company’s proprietary Kata Bot Platform can be leveraged to create feature-rich chatbots on top of Kata.ai’s robust and scalable AI technology platform, ensuring company of any size can easily build their own chatbot on any messaging platform. With this platform, it is now possible for the business to focus on designing engaging interaction for their customers, while Kata.ai handles all the technology aspects of the chatbots. Established in 2015, the company has become a trusted partner for major corporations such as Microsoft, Accenture, and Line. In 2020, the company received Series-B funding from TransPacific Technology Fund and MDI Venture. Job Description You will design, build, and deploy production-grade AI systems — including LLM-powered conversational agents, RAG pipelines, NLP workflows, and voice AI integrations — to deliver intelligent, reliable, and measurable AI solutions for enterprise clients across government, financial services, healthcare, and telecommunications sectors — so that Kata's clients can automate customer interactions at scale with high accuracy, low latency, and strong business impact. Qualifications Qualifications & Education : - 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 Technical Skills : - LLM Integration: OpenAI GPT-4o, Anthropic Claude, Google Gemini, or open-source models (LLaMA, Mistral, Qwen) - AI Frameworks: LangChain, LlamaIndex, CrewAI, or similar agent/RAG orchestration frameworks - Prompt Engineering: System prompt design, few-shot prompting, chain-of-thought, structured output (JSON mode, function calling) - RAG Pipelines: Document chunking, embedding strategies, retrieval optimization, reranking - Vector Databases: Pinecone, Weaviate, Qdrant, or pgvector - Voice AI: LiveKit Agents SDK, STT integrations (Deepgram, Google Speech-to-Text, Whisper), TTS integrations (ElevenLabs, Google TTS) - Languages: Python (required); FastAPI for AI service exposure - Cloud: GCP or Azure for AI/ML workload deployment — Vertex AI, Azure OpenAI, Cloud Run - Evaluation Frameworks: RAGAS, DeepEval, custom eval pipelines, or LLM-as-judge approaches - Containerization: Docker; basic Kubernetes for deploying AI services - Monitoring: AI-specific observability — LangSmith, Langfuse, or custom logging for tracing LLM calls in production Experience Associate Level (1–2 years) - 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 Mid Level (3–5 years) - 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 Additional Information We value a flexible working hour for our employees. The most important is we provide a learning experience in Conversational AI Industry.