Role & Key Responsibilities

Implement conversational agent features using LLMs and voice integration
Develop real-time conversational flows (intent detection, slot extraction, fallback handling, barge-in rules)
Integrate Azure Cognitive Services (Speech-to-Text, Text-to-Speech, Language Services) and open-source AI components
Build and optimize pipelines for secure data handling (PII masking, transcript storage, session persistence)
Implement monitoring and logging for model performance and conversation quality
Ensure compliance with enterprise-level security and privacy requirements during implementation

Technical Skills

Voice AI: Speech-to-Text and Text-to-Speech integration (Azure Speech Services/Open Source), orchestration of voice agents
LLM & NLP: experience with LLMs; intent classification, slot extraction, summarization
MLOps: Azure ML, Databricks
Evaluation & Testing: defining metrics for conversational AI (intent accuracy, fallback rate, voice consistency, hallucination control)

Experience Required

23 years in AI/ML software development, with focus on conversational AI or NLP applications
Hands-on experience with Azure AI services in production systems
Previous work on real-time systems

AI Developer