AI Developer (AI Voice Agent)

AMZ - ALLSTARS OPC; Makati; On-site; PHP 900,000 - 1,900,000; Full time

Job summary

AMZ - ALLSTARS OPC in Philippines is seeking a hands-on AI Voice Engineer to design, build, deploy, and scale real-time AI voice calling solutions. You will integrate telephony, STT, LLMs, and TTS to power natural conversations and ensure low latency at scale.

This production-focused role requires crafting reliable infrastructure, implementing monitoring, and collaborating with client teams to optimize performance and costs as demand grows.

Qualifications

• 3+ years as AI Developer or related role.
• At least 1 year deploying AI voice systems in production.
• Experience with telephony, STT, LLMs, and TTS in real-time.
• Ability to scale systems and manage latency.

Responsibilities

• Design, build, test, and deploy AI voice calling workflows.
• Integrate real-time voice tech for low latency and accuracy.
• Extend the platform for patient and insurance calls.
• Monitor performance, diagnose latency issues, and improve reliability.
• Document call flows and configurations for maintainability.

Skills

Real-time voice work

Telephony integration

Latency optimization

Problem-solving

Education

Bachelor's degree in CS or related field

Tools

Speech-to-Text (STT)

Text-to-Speech (TTS)

LLMs

Monitoring/Observability tools

VoIP/Telephony APIs

Job description

You will turn AI voice calling from a promising idea into a reliable, scalable production system that delivers natural, real-time conversations between AI voice agents and callers. You will build and optimize the end-to-end voice pipeline, integrating telephony, speech recognition, AI models, and voice synthesis to create seamless conversational experiences. Your work will ensure the system can support up to 100,000 AI calls while maintaining performance, reliability, and conversation quality as the client’s business grows. By addressing latency, scalability, and system reliability, you will transform AI voice automation into a dependable solution ready for real-world production.

Role Overview:

We are looking for a hands-on AI Voice Engineer to design, build, deploy, and scale real-time AI voice calling solutions for our client. This is a production-focused role where you will:

• Build the end-to-end voice pipeline: Integrate telephony services, speech-to-text (STT), large language models (LLMs), text-to-speech (TTS), and backend systems to power real-time AI conversations.

• Design for scalability: Architect and optimize the infrastructure to support up to 100,000 AI calls, with capacity for the required call volume and concurrency.

• Optimize conversational performance: Minimize response latency and improve speech recognition, turn-taking, interruption handling, and overall voice quality.

• Ensure production reliability: Implement monitoring, testing, error handling, and recovery mechanisms to maintain system stability and call quality at scale.

• Continuously improve the platform: Troubleshoot issues, optimize infrastructure and operating costs, and strengthen the system as the client’s needs evolve.

Key Responsibilities:

Voice Agent Development

• Design, build, test, and deploy AI voice calling workflows.

• Integrate and optimize real-time voice technologies for low latency, accurate speech recognition, and natural conversational responses.

• Implement streaming audio, turn-taking, interruption handling, and conversation state management.

Call Automation

• Extend the voice platform to automate patient and insurance calls.

• Develop conversational flows, escalation paths, and fallback behavior for real-world calling scenarios.

• Integrate with relevant APIs, databases, and business systems as required.

Scalability and Reliability

• Architect for high call volumes, including concurrency management, queuing, retries, rate limits, and provider constraints.

• Monitor production performance and diagnose issues involving latency, failed or dropped calls, and interruptions.

• Implement logging, monitoring, testing, and recovery mechanisms to improve system reliability.

Collaboration and Ownership

• Work closely with the client team, maintaining meaningful overlap with their working hours.

• Take ownership of deployment, monitoring, troubleshooting, and ongoing improvements.

• Document call flows, system configurations, technical decisions, and lessons learned to support maintainability and scale.

Required Experience

• 3+ years of experience as an AI Developer, AI Voice Engineer, Solutions Engineer, or in a closely related engineering role.

• At least 1 year of experience deploying and operating AI voice calling systems in production.

• Hands-on experience building and integrating real-time voice stacks involving telephony, STT, LLMs, and TTS.

• Demonstrated experience diagnosing and resolving production scaling issues, with concrete examples of problems encountered and solutions implemented.

• Understanding of concurrency, rate limits, asynchronous processing, retries, and fault tolerance in high-volume systems.

• Ability to design, troubleshoot, and optimize voice agents beyond the prototype stage.

Preferred Qualifications

• Experience with healthcare, revenue cycle management (RCM), insurance, or other regulated call workflows.

• Experience with high-volume outbound calling, including pacing, concurrency controls, and retry logic.

• Familiarity with monitoring, observability, and evaluation tools for AI voice agents.

• Experience integrating voice agents with CRMs, scheduling systems, APIs, or other enterprise platforms.

• Experience optimizing latency, reliability, and cost in production AI systems.

What You’ll Bring to the Team

• Ownership mindset: You take responsibility for shipping, monitoring, troubleshooting, and improving production systems.

• Strong problem-solving skills: You can diagnose complex issues, identify root causes, and implement practical, lasting solutions.

• Clear communication: You communicate technical decisions and progress effectively and work well with a remote team.

• Engineering judgment: You make sound trade-offs between speed, quality, reliability, and cost.

• Adaptability: You learn quickly, work independently, and respond effectively to changing requirements.