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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Engineer - Robot Applications & Voice AI - **Company:** Cerence Inc. - **Location:** San Francisco Bay Area, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $166,000.0 - $264,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Applications Architecture, Application Layers, Automated Storage and Retrieval Systems, Automation of Tests, Microsoft Azure, Beamforming, C++ (Programming Language), Cloud Computing, Software Quality, Computer Programming, Continuous Integration, Software Debugging, Hardware Design, Python (Programming Language), Object Detection, Software Construction, Software Engineering, Systems Integration, Core Voice Platform, Data Logging, Enterprise Software Applications, Large Language Models, Multi-Agent Systems, State Machines, Software Application Programming, Event Driven Architecture, Containerization, AI Platforms, Kubernetes, Machine Learning Operations, Virtual Agents, Api Design, Natural Language Understanding, Docker - **Published:** July 23, 2026 - **Apply:** https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---USA/Principal-Software-Engineer---Robot-Applications---Voice-AI_R0005992 ## About the Role Mandatory (Must Have) * Orchestration & Logic Frameworks: Strong proficiency in BehaviorTree.CPP, state machines, workflow orchestration engines, or task-planning architectures. * Cognitive AI & Agent Systems: Hands-on experience building applications using LLMs, VLMs, tool-calling architectures, agent frameworks, RAG systems, or semantic memory platforms. * Programming: 5+ years of professional software engineering experience using Python and/or C++. * Application Architecture: Experience designing scalable application-layer software, API-driven systems, distributed services, and event-driven architectures. * Edge Compute Management: Experience optimizing software on resource-constrained edge hardware under intermittent connectivity conditions. * Cloud & AI Services: Experience integrating cloud AI services, model serving platforms, and containerized deployments. * Software Quality & Production Delivery: Automated testing, debugging, monitoring, observability, and CI/CD practices. * Human-Robot Interaction Mindset: Experience designing natural, context-aware human-machine experiences. Good to Have (Highly Valued Plus) * Voice & Speech Stack: Cerence, Whisper, Deepgram, Azure Speech, ElevenLabs, AWS Speech Services, STT/TTS/NLU platforms. * Robotics Framework Consumption: ROS2 application nodes, Services, Actions, Topics, navigation and manipulation APIs. * Vision & Multi-Modal AI: Object detection, scene understanding, visual grounding, and spatial reasoning systems. * Audio Hardware Integration: Beamforming, Acoustic Echo Cancellation (AEC), microphone arrays, and noise suppression. * Physical AI Applications: Experience building software for humanoids, service robots, warehouse automation, or embodied AI systems. * Data & Learning Pipelines: Telemetry, analytics, evaluation systems, retraining pipelines, and AI feedback loops. * Containerization & Deployment: Docker, Kubernetes, OTA updates, and edge deployment environments. * Startup Environment: Comfortable owning solutions from concept through deployment in a fast-moving environment., * Bachelor's or Master's degree in Computer Science, Robotics, Software Engineering, AI, or a related discipline. ## Description Application Layer & Business Logic: Implement high-level application software, interaction workflows, and robotic behavioral state machines. Intent-to-Action Orchestration: Build the core logic that translates human speech, gestures, environmental cues, and contextual information into deterministic robotic tasks. Multi-Modal Interaction Fusion: Integrate vision pipelines, object detection, scene understanding, spatial tracking, and voice interactions to provide contextual awareness. Voice Application Engineering: Develop robust voice applications managing STT, NLU, dialog management, wake-word detection, and TTS interfaces. Agentic AI Development: Build orchestration workflows combining LLMs, VLMs, memory systems, tool calling, reasoning engines, and robotic capabilities. Robot Capability Integration: Consume and orchestrate navigation, manipulation, perception, and device-control services exposed by the robotics platform. Edge/Cloud Partitioning: Optimize applications to balance low-latency local execution with cloud-based AI services. Multi-Device & Ecosystem Integrations: Integrate robots with mobile devices, smart home ecosystems, enterprise applications, and cloud APIs. Data Loop Contribution: Build telemetry, logging, and evaluation mechanisms supporting continuous model improvement. Deployment & Production Readiness: Contribute to testing, observability, CI/CD, and production deployment practices., All prospective and current Employees need to remain vigilant when it comes to executing security policies in the workplace. This includes: - Following workplace security protocols and training programs to familiarize with the ways to maintain a safe workplace. - Following security procedures to report any suspicious activity. - Having respect for corporate security procedures to allow those procedures to be effective. - Adhering to company's compliance and regulations. - Encouraging to follow a zero tolerance for workplace violence. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [API Design - Getting Started](https://www.wearedevelopers.com/videos/33-api-design-getting-started) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Robots are coming into the wild! 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