Principal Software Engineer – Robot Applications & Voice AI

Cerence

2d•$165,550 - $264,450•Hybrid

About The Position

Cerence is building the cognitive and application layer that combines Voice AI, Agentic AI, multimodal reasoning, and robotic capabilities into intuitive human-robot experiences. The Principal Software Engineer drives the application and cognitive layer of our humanoid robot. Working directly with the core robotics platform designed by our Architect, you will turn human intent into high-level physical actions. This role focuses on building advanced voice applications, multi-modal context systems, and programming the core business logic and behavior trees that make the robot interactive, helpful, and intuitive.

Requirements

Strong proficiency in BehaviorTree.CPP, state machines, workflow orchestration engines, or task-planning architectures.
Hands-on experience building applications using LLMs, VLMs, tool-calling architectures, agent frameworks, RAG systems, or semantic memory platforms.
5+ years of professional software engineering experience using Python and/or C++.
Experience designing scalable application-layer software, API-driven systems, distributed services, and event-driven architectures.
Experience optimizing software on resource-constrained edge hardware under intermittent connectivity conditions.
Experience integrating cloud AI services, model serving platforms, and containerized deployments.
Automated testing, debugging, monitoring, observability, and CI/CD practices.
Experience designing natural, context-aware human-machine experiences.

Nice To Haves

Cerence, Whisper, Deepgram, Azure Speech, ElevenLabs, AWS Speech Services, STT/TTS/NLU platforms.
ROS2 application nodes, Services, Actions, Topics, navigation and manipulation APIs.
Object detection, scene understanding, visual grounding, and spatial reasoning systems.
Beamforming, Acoustic Echo Cancellation (AEC), microphone arrays, and noise suppression.
Experience building software for humanoids, service robots, warehouse automation, or embodied AI systems.
Telemetry, analytics, evaluation systems, retraining pipelines, and AI feedback loops.
Docker, Kubernetes, OTA updates, and edge deployment environments.
Comfortable owning solutions from concept through deployment in a fast-moving environment.

Responsibilities

Implement high-level application software, interaction workflows, and robotic behavioral state machines.
Build the core logic that translates human speech, gestures, environmental cues, and contextual information into deterministic robotic tasks.
Integrate vision pipelines, object detection, scene understanding, spatial tracking, and voice interactions to provide contextual awareness.
Develop robust voice applications managing STT, NLU, dialog management, wake-word detection, and TTS interfaces.
Build orchestration workflows combining LLMs, VLMs, memory systems, tool calling, reasoning engines, and robotic capabilities.
Consume and orchestrate navigation, manipulation, perception, and device-control services exposed by the robotics platform.
Optimize applications to balance low-latency local execution with cloud-based AI services.
Integrate robots with mobile devices, smart home ecosystems, enterprise applications, and cloud APIs.
Build telemetry, logging, and evaluation mechanisms supporting continuous model improvement.
Contribute to testing, observability, CI/CD, and production deployment practices.