AI Engineer (Full-time)

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 Katas clients can automate customer interactions at scale with high accuracy low latency and strong business impact.

Qualifications :

Qualifications & Education : 

• Bachelors degree in Computer Science Artificial Intelligence Data Science Computational Linguistics or related field
• Masters degree in AI/ML is a plus
• Relevant certifications (GCP AI/ML 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 (12 years)

• 12 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 (35 years)

• 35 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.

Remote Work :

Yes

Employment Type :

Full-time