#Windows Audio Software Engineer (Voice AI) — Engineer

Originally posted 10 September 2026 by the employer.

Design and build on-device Voice AI capabilities on Windows-on-Snapdragon platforms.

About the role

This role involves designing and building on-device Voice AI capabilities on Windows-on-Snapdragon platforms, spanning low-power "always-on" sensing through interactive speech experiences.

What you'll do

• Own feature development for Voice AI capabilities on Windows, including wake-on-voice, on-device ASR, translation, transcription, and TTS.
• Gather and refine technical requirements with internal and external partners; translate product goals into clear engineering requirements, architecture, and milestones.
• Co-design and implement Windows audio driver stack solutions that leverage Qualcomm SoC CPU/DSP/NPU capabilities while meeting strict latency and power targets for Voice AI experiences.
• Build or extend components across user-mode and kernel-mode boundaries (UMDF/KMDF), integrating with Windows audio frameworks and platform services for Voice AI pipelines.
• Drive low-power audio architecture for "always-on" use cases, including concurrency and power-mode transitions across multiple audio features.
• Optimize and validate performance using Windows diagnostics and systematically debug complex multi-threaded and multi-processor issues across HW/SW boundaries.

What you'll need

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.
• Proficiency in systems programming (C/C++ preferred) and ability to deliver production-quality code in complex codebases.
• Strong Windows development skills using Visual Studio, source control (Git-based workflows), and disciplined debugging practices.
• Solid understanding of Windows OS fundamentals relevant to system-level development: processes/threads, synchronization primitives, memory, I/O, and performance diagnostics.
• Experience developing or integrating Windows drivers using KMDF and/or UMDF, including build, deployment, and debugging fundamentals.
• Hands-on experience with multi-threaded programming, concurrency control, and performance/latency tuning.

Nice to have

• Master's Degree in Engineering, Information Systems, Computer Science or related field.
• 2 years of industry experience in software engineering, with a focus in one or more of the following areas: Windows system software, device drivers, multimedia/audio, platform software, or performance/power-sensitive products.
• Windows audio ecosystem experience (any of the following): audio drivers, audio endpoints, WASAPI, audio effects/APOs, audio policy, power-aware audio scenarios, or end-to-end audio pipeline integration.
• Demonstrated experience using AI-assisted development tools to improve productivity across the software lifecycle, with the ability to iterate on prompts and validate outputs against real code and requirements.
• Familiarity with mainstream AI coding assistants (e.g., GitHub Copilot / Microsoft Copilot) applied to practical engineering tasks such as code comprehension, change drafting, test scaffolding ideas, and documentation.
• Ability to create and share repeatable prompt patterns/templates for common engineering workflows and continuously refine prompts to increase specificity and accuracy.
• Experience with low-power / always-on audio and power-state transitions (e.g., Modern Standby constraints and wake/trigger flows).
• Familiarity with on-device voice activation building blocks and staged verification concepts (e.g., multi-stage keyword/wake approaches).
• Experience optimizing workloads across heterogeneous compute (CPU DSP NPU) and understanding tradeoffs across latency vs. power vs. quality.
• Exposure to Voice AI pipelines: ASR/TTS, speech translation, transcription, streaming/buffering strategies, and real-time constraints.

Skills: Windows audio driver stack, user-mode and kernel-mode, low-power audio architecture, heterogeneous compute (CPU/DSP/NPU), Voice AI pipelines