- Design, develop, and deploy sophisticated conversational AI experiences leveraging LLMs, ensuring seamless user interaction and accurate responses.
- Implement and optimize Retrieval Augmented Generation (RAG) pipelines to enhance LLM knowledge bases with domain-specific information and real-time data.
- Build and manage AI agents capable of complex task execution, decision-making, and autonomous operation within defined parameters.
- Fine-tune and adapt pre-trained large language models for specific conversational AI applications, optimizing for performance, relevance, and safety.
Desired Candidate Profile
Strong foundational AI/ML concepts
RAG (Retrieval Augmented Generation) architectures
Embeddings & vector search
Data/document ingestion strategies
Agent & Agentic AI design patterns
Orchestrator-based multi-agent systems
Agent registry & A2A (Agent-to-Agent) protocol
Conversational AI development
Journey/goal mapping and intent routing