Sr. AI Voice Engineer

Knight Insurance Group•Los Angeles, CA

17d•Onsite

About The Position

This role involves working with state-of-the-art speech recognition, speech synthesis, voice streaming, and AI agent frameworks to create scalable voice solutions for customer service, sales, finance, and automation applications. This is an on-site position with no relocation assistance provided. If you're passionate about conversational AI and enjoy solving challenging engineering problems, we'd love to hear from you.

Requirements

Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
5+ years of professional software engineering experience.
Hands-on experience building voice-to-voice AI applications.
Strong understanding of: Speech Recognition (Automatic Speech Recognition - ASR), Speech Synthesis (Text-to-Speech - TTS), Voice Activity Detection (VAD), Audio streaming and low-latency communication.
Professional experience with Python and C#/.NET.
Experience consuming AI APIs and working with LLMs.
Experience building REST APIs and microservices.
Knowledge of asynchronous programming, event-driven architectures, and real-time streaming.
Strong debugging, analytical, and problem-solving skills.

Nice To Haves

Experience with one or more of the following: Real-time conversational AI platforms, AI agent frameworks, Retrieval-Augmented Generation (RAG), Vector databases, Prompt engineering and evaluation, WebRTC, SIP, RTP, or telephony integrations, Azure AI, Azure OpenAI, or other cloud AI services, Docker and Kubernetes, CI/CD pipelines and cloud-native application development.

Responsibilities

Design and develop real-time voice-to-voice AI agents.
Build conversational AI systems using LLMs and agent frameworks.
Integrate Speech-to-Text (STT) and Text-to-Speech (TTS) technologies into production applications.
Optimize latency and streaming performance for natural conversations.
Develop backend services and APIs using Python and C#/.NET.
Integrate with telephony, voice streaming, and communication platforms.
Implement conversation memory, tool calling, function execution, and retrieval-augmented generation (RAG) workflows.
Collaborate with product managers, AI engineers, and software developers to deliver production-ready AI solutions.
Evaluate emerging AI models, speech technologies, and voice platforms.
Monitor, troubleshoot, and continuously improve voice agent performance and reliability.