Senior Audio Software Engineer

People in AI; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

People in AI is seeking a Senior Software Engineer, Audio to own and build real-time audio systems, integrating speech recognition, language models, and speech synthesis. The role combines streaming infrastructure with backend services and applied AI to deliver faster, more reliable conversational experiences.

You will work across streaming workflows, production services, and live communication APIs, with opportunities to influence architecture and decisions.

Qualifications

• Hands-on software engineer with production applications experience.

Responsibilities

• Build real-time audio systems linking speech recognition, language models, and speech synthesis.
• Create Python-based services that manage sessions, interruptions, and multi-party interactions.
• Improve audio performance by addressing latency, noise, and speaker IDs.
• Engineer reliable backends with APIs and event-driven services.
• Handle edge cases with recovery when speech is unclear or conversations change.
• Own features from design to deployment, monitoring, and improvement.
• Collaborate with product and AI teams to improve conversational experiences.

Skills

Python

Go

WebRTC

Speech recognition

Speech synthesis

Async programming

API development

Streaming architectures

Tools

WebRTC frameworks

Streaming platforms

Job description

Location: Remote - USA

Employment Type: Full-time

Build real-time audio technology that makes complex conversations feel natural.

Our client is developing AI-powered communication software used in real-world environments where clarity, speed, and reliability are essential.

The engineering challenges go well beyond connecting speech models together. The team is solving problems around streaming audio, interruptions, speaker changes, background noise, and the unpredictable nature of live conversation.

They're looking for a Senior Software Engineer, Audio to take substantial ownership of the systems behind these experiences.

The Opportunity

This is a hands‑on software engineering role combining real-time audio, backend systems, and applied AI.

You'll work across streaming infrastructure, conversational workflows, and production services. You'll help make the product faster, more resilient, and easier to use, with direct influence over architecture and technical decisions.

The team offers the ownership of a small engineering group alongside the resources and reach of a larger organization.

What You'll Do

• Build real-time audio systems: Develop streaming workflows connecting speech recognition, language models, and speech synthesis.
• Create conversational applications: Build Python-based services that manage sessions, interruptions, and multi‑party interactions.
• Improve audio performance: Address latency, noisy environments, speaker identification, and conversational turn‑taking.
• Engineer reliable backends: Develop APIs and event‑driven services that support live communication.
• Handle difficult edge cases: Build sensible recovery behavior when speech is unclear, services fail, or conversations change direction.
• Own delivery: Take features from architectural decisions through implementation, deployment, monitoring, and improvement.
• Work closely with product and AI teams: Turn user feedback into better conversational experiences.

What You'll Bring

• Strong software engineering experience building and maintaining production applications.
• Practical experience with real-time audio, voice AI, conversational systems, or streaming applications.
• Strong Python, including asynchronous programming and production API development.
• Solid backend engineering fundamentals and experience with Go, or the ability to become productive in it quickly.
• Familiarity with WebRTC, telephony, streaming architectures, or real‑time communication frameworks.
• Experience integrating speech recognition, speech synthesis, or language model services.
• Confidence debugging performance and reliability issues across multiple services.
• A product mindset and the ability to own substantial technical work independently.