Senior AI Engineer

We seek a forward-thinking Senior AI Engineer who has strong domain knowledge of implement AI first solutions for consumer facing product. The candidate will work directly with the Founder in developing a new-age product in the Insurance space, which has the potential to generate $10B in revenues at scale (a first-of-its-kind, but a much-needed innovation).

Key Responsibilities:

• Model Development & Deployment: Architect, develop, train, and deploy advanced AI/Machine Learning models for various applications. This will involve selecting appropriate model architectures (e.g., deep learning, traditional ML), optimizing model performance, and ensuring scalability and reliability in production environments.
• Conversational AI Development (Voice and Chat) : Design, build, and optimize a sophisticated conversational AI agent specifically for selling health insurance products. This includes:
  • Developing dialogue management systems that guide users through the sales funnel.
  • Implementing intent recognition and entity extraction models tailored to health insurance queries and sales interactions.
  • Crafting compelling and compliant sales responses that address customer needs, handle objections, and provide accurate product information.
  • Ensuring the AI can effectively qualify leads, explain complex policy details, and guide users towards conversion.
• Prompt Engineering & Dialogue Flow Optimization: Design and optimize prompts for large language models (LLMs) to achieve desired outcomes for specific business use cases, with a strong emphasis on natural, persuasive, and effective sales conversations. This includes developing robust strategies for managing complex conversation flows, ensuring seamless transitions, and maintaining context throughout the interaction.
• Evaluation Criteria & Validation: Define and implement rigorous evaluation criteria across the entire AI pipeline, from dataset creation to model validation. This includes establishing metrics for data quality, model performance, bias detection, and ensuring robust validation strategies to build trustworthy and reliable AI systems. For conversational AI, this will also include metrics for dialogue success, user satisfaction, conversion rates, and adherence to sales scripts/compliance.
• Data Science & Engineering Excellence: Apply strong data science principles to analyze complex data, extract insights, and formulate data-driven solutions. Demonstrate proficiency in data engineering practices, including building scalable data pipelines, managing data infrastructure, and ensuring efficient data access for AI development.
• Research & Innovation: Stay abreast of the latest advancements in AI, machine learning, and fintech/insurance domains, actively exploring and integrating new technologies and methodologies to enhance our AI capabilities, particularly in the realm of conversational sales.

Interview Process

3 rounds of interaction, will include 1 round of hands-on.