The Applied AI Engineer on our AI team is responsible for building and improving production-grade Voice AI systems that enable natural, reliable, and scalable AI-powered phone conversations.

You will work on the complete lifecycle of conversational AI experiences, from integrating speech-to-text, text-to-speech, and large language models into real-time applications, to improving conversation quality, latency, reliability, and operational performance.

This role combines applied AI engineering with strong backend and systems skills. You will work with existing AI infrastructure, extend the platform capabilities, solve complex real-time challenges, and own features end-to-end from design and implementation to deployment, monitoring, and continuous improvement.

The goal of this role is to build robust Voice AI systems that can handle real-world conversations at scale, with a strong focus on user experience, response quality, latency, and reliability.

Key Responsibilities

Build and improve Voice AI experiences

• Design and develop production systems that integrate speech-to-text (ASR), text-to-speech (TTS), conversational AI models, and voice agents.
• Improve the quality and naturalness of AI conversations, including turn-taking, interruption handling, and conversation flow.
• Evaluate and optimize AI model performance based on real-world usage and measurable quality metrics.
• Work on challenges such as latency reduction, response quality, and robustness in noisy real-world environments.

Develop reliable real-time AI systems

• Build and maintain backend services that support real-time voice interactions at scale.
• Design reliable asynchronous workflows for processing calls, events, and AI interactions.
• Ensure systems are resilient through proper handling of failures, retries, state management, and observability.
• Work with existing telephony and AI infrastructure to extend capabilities and improve system performance.

Own features end-to-end

• Take ownership of AI product features from initial design and technical decisions to implementation, deployment, monitoring, and iteration.
• Investigate production issues using logs, metrics, recordings, and system data.
• Make data-driven decisions by measuring system behavior and identifying bottlenecks.

Required Skills

• Strong Python programming skills.
• Experience building production backend services.
• Good understanding of asynchronous programming and real-time systems.
• Experience with APIs, databases, and event-driven architectures.
• Experience with testing, debugging, and maintaining production systems.
• Applied AI & Speech Systems
• Experience integrating AI models or AI APIs into production applications.
• Understanding of speech AI concepts including ASR, TTS, voice agents, and conversational AI.

Preferred Experience

• Experience working with streaming AI APIs or real-time model interactions.
• Experience with audio processing concepts such as PCM, sampling rates, resampling, and voice activity detection.
• Experience with VoIP systems such as SIP, RTP, Asterisk, or similar platforms.
• Experience with Redis, PostgreSQL, message queues, or event streaming systems.