Conversation AI Engineer

Own the design and implementation of the agentic conversational AI layer, including intent detection, dialogue orchestration, and multi-step reasoning across chat, phone, and ecommerce channels.

Build real-time AI advisor assist tools that leverage LLMs for context injection, tool-calling, and response suggestion aligned with advisor workflows.

Define and monitor conversation quality metrics and operate continuous improvement loops using real interaction data and probabilistic fallback handling for low-confidence or ambiguous inputs.

3–5 years experience in conversational AI, NLP engineering, or LLM-based product development.

Proficiency in Python and NLP tooling with strong knowledge of intent classification, entity extraction, and context management in stateful conversations.

Experience deploying conversational AI systems to production with real user traffic and handling uncertainty with confidence scoring and fallback mechanisms.

Work Experience Required: 3–5 years in relevant fields; Notice Period: Not explicitly mentioned in the JD.

Demonstrated ability to architect conversation systems aligned to real business processes rather than scripted flows.

Experience with probabilistic reasoning approaches in conversation design to manage intent ambiguity and confidence.

Skilled in data-driven iteration using defined conversation quality metrics and evaluation datasets derived from actual user interactions.