Employment Type : Full-time

Job Summary :

We are seeking a highly skilled Conversational AI Engineer with 5- 7 years of experience and strong expertise in Large Language Models (LLMs), Voice Bots, and Generative AI. This role is pivotal in designing, building, and deploying next-generation intelligent voice solutions for our insurance operations, focusing on leveraging LLMs for advanced conversational capabilities, contextual accuracy, and seamless integration with core enterprise systems.

Key Responsibilities and Technical Focus :

LLM Design and Development :

- Design and develop advanced conversational AI solutions using LLMs for intelligent voice bot interactions, driving complexity and capability beyond traditional NLU models.

- Implement advanced techniques like Prompt Engineering and RAG (Retrieval-Augmented Generation) architectures to significantly improve contextual understanding and response accuracy for domain-specific queries.

- Fine-tune and optimize LLMs for specific insurance voice conversations, including tasks like intent classification, entity extraction, and sentiment analysis.

Voice Bot Architecture & Deployment :

- Architect and deploy enterprise-grade voice bots using industry-leading platforms such as Genesys Cloud Architect, Amazon Lex, and Google Dialogflow.

- Utilize orchestration frameworks like LangChain and LlamaIndex for building complex, multi-step conversational flows and integrating external data sources.

STT/TTS and Orchestration :

- Build robust STT/TTS (Speech-to-Text / Text-to-Speech) pipelines using state-of-the-art models such as Whisper, Azure Speech Services, and Google Speech API.

- Develop sophisticated conversational agents with memory, context retention, and personalization features.

- Build LLM orchestration layers to efficiently manage API calls, database queries, and third-party integrations needed during complex conversations.

Integration, NLU, and Compliance :

- Integrate voice bots with backend systems using RESTful APIs and event-driven architectures for real-time data retrieval and transaction processing.

- Enhance core NLU capabilities by leveraging transformer models and implementing custom entity recognition techniques.

- Ensure all voice interactions and data handling processes rigorously follow major data privacy and security standards, including GDPR, CCPA, and HIPAA.

Required Qualifications & Skills :

- Experience : 5- 7 years of hands-on experience in Conversational AI, NLP, and Voice Bot development.

- LLM/GenAI : Strong technical expertise in designing and deploying solutions leveraging LLMs (Large Language Models) and Generative AI principles.

- Voice Platform Mastery : Hands-on experience architecting and deploying voice bots using at least one major platform (Genesys Cloud Architect, Amazon Lex, or Google Dialogflow).

- Orchestration : Experience implementing and utilizing LLM orchestration frameworks like LangChain or LlamaIndex.

- Core NLP/ML : Proficiency in techniques such as intent classification, entity extraction, RAG, and fine-tuning transformer models.

- STT/TTS : Practical experience building and optimizing pipelines using major speech recognition models/services (e.g., Whisper, Azure Speech, Google Speech).

- Integration : Strong ability to integrate conversational agents with enterprise backend systems via RESTful APIs and event-driven patterns.

- Compliance : Demonstrated understanding of data privacy regulations (GDPR, CCPA, HIPAA) as they apply to voice data.

Preferred Skills :

- Experience working specifically within the Insurance or Financial Services industry.

- Proficiency in Python and relevant data science libraries.

- Certification in relevant cloud platforms (e.g., AWS Certified Machine Learning, Google Cloud Engineer).

- Experience with MLOps practices for deploying and monitoring conversational models at scale.