# Lead Embedded Software Engineer **Company**: Logitech **Location**: Suzhou **Work arrangement**: remote **Experience**: senior **Job type**: full-time **Category**: Engineering **Industry**: Technology **Wikidata**: https://www.wikidata.org/wiki/Q223127 **Apply**: https://logitech.wd5.myworkdayjobs.com/en-US/Logitech/job/Suzhou-China/Lead-Embedded-Software-Engineer_146647-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_b6adef29-060 ## Description We are seeking a Lead Embedded Software Engineer to lead software and AI exploration and development for AI-embedded smart hardware and software, keyboards, mice, gaming peripherals, and IoT devices. You will own the software stack that makes hardware intelligent: on-device ML for personalization and predictive input, LLM-backed companion app features, and natural language device control across edge, app, and cloud. Key Responsibilities: AI Agent Integration & Feature Development - Develop on-device AI features for smart peripherals (input personalization, predictive shortcuts, gesture/intent classification, adaptive behavior driven by usage patterns) - Build LLM-backed companion app features (natural language device configuration, AI assistant integration, conversational automation and settings control) - Integrate AI agent frameworks into the product stack to deliver and orchestrate smart hardware features across device, companion app, and cloud - Integrate the AI agent with chat/messaging platforms (e.g., Feishu, WeChat, Telegram, Discord) for remote device control, status notifications, and event-driven automation Device Management & Cloud Platform - Design and implement the device management backend: provisioning, settings sync, OTA distribution, and companion app APIs - Build the telemetry pipeline: ingest sensor/usage events from devices, feeding product analytics and AI model improvement loops - Integrate China-local LLM and AI service providers for companion app AI features; implement provider abstraction with config-driven failover and secure API key management - Achieve <.5s end-to-end response latency from user request to AI feature delivery, using streaming APIs and edge-optimized provider routing LLM & AI Provider Integration - Configure the multi-provider LLM architecture for China-local providers as primary (MiniMax, Qwen, Kimi, DeepSeek, Zhipu AI) supporting companion app AI features and natural language device control - International providers (Claude, GPT) as fallback - Implement provider switching via config (no code change), secure API key management, and graceful fallback when primary LLM is unavailable Sensor Integration & Signal Processing - Integrate optical sensors, hall-effect/TMR sensors, IMU, haptic actuators, or microphones into a software-controlled AI feature pipeline (e.g., adaptive input, gesture recognition, ambient awareness) - Expose sensor data streams to on-device AI models and companion app cloud services for real-time inference - Collaborate with HW/EE engineer on sensor calibration, signal conditioning, and device protocol data formats Hardware-Software Interface - Work closely with EE/firmware engineer to define the USB/BLE/I2C/UART communication protocol between the peripheral MCU and the host-side software stack - Implement the host-side Hardware Controller layer: translate high-level AI feature commands (e.g., “set haptic pattern X”, “trigger RGB effect”) into device protocol messages - Implement real-time device state feedback (latency, battery, sensor readings) consumed by the companion app and AI agent for adaptive behavior - Implement physical feedback behaviors (haptic patterns, audio cues, LED indicators) triggered by AI agent decisions or user notifications Required Qualifications Technical Skills - Programming Languages: Proficient in Node.js/JavaScript and Python; comfortable with C or C++ (for reading protocol specs and writing lightweight host-side native modules) - AI Agent Platforms: Hands-on experience with AI agent frameworks (e.g., LangChain, LangGraph, Pipecat, or similar), including creating custom skills/plugins for product feature delivery - Embedded Linux: Experience developing software on ARM-based SBCs (Raspberry Pi, Orange Pi, Jetson Orin Nano, etc.) - LLM APIs: Practical experience integrating LLM provider APIs , especially China-local providers (MiniMax, Qwen, Kimi, DeepSeek) - Backend Development: REST/WebSocket APIs for companion apps, device provisioning, and cloud integration for AI-powered smart hardware features - Sensor & Signal Processing: Basic experience with sensor data pipelines (IMU fusion, optical flow, audio signal processing, or OpenCV/MediaPipe) - Linux Systems: Comfortable with Linux system administration, systemd services, udev rules, USB/HID debugging, and profiling on resource-constrained ARM hardware Experience - 5+ years of software development experience - 1+ year working with Linux application development (system services, daemons, IPC, process management) - 1+ year working with LLM-based applications or AI agent systems - Demonstrated experience with at least one smart hardware, IoT, or physical computing project - Experience with real-time signal processing on embedded platforms Preferred Qualifications - Experience with Dify, LangGraph, or MCP (Model Context Protocol) for building tool-integrated agent pipelines - Experience with chat platform API integration (e.g., WeChat, Feishu, Telegram, Discord) - Knowledge of HID protocols (USB HID, BLE HID/HOGP) and peripheral MCU communication (UART, SPI, I2C, USB CDC-ACM) - Experience with embedded display integration (LVGL, SDL2, or framebuffer) for smart peripheral UIs - Experience building web-based companion app configuration UIs (device settings, OTA trigger, provisioning) - Experience with OTA firmware distribution (staged rollouts, A/B cohorting, rollback) - Chinese language proficiency (for coordinating with China-based vendors and LLM providers) - Prior experience with AI robot, voice companion, or social robot products is a plus ## Skills ### Required - Node.js - JavaScript - Python - C - C++ - LangChain - LangGraph - Pipecat - Embedded Linux - LLM APIs - REST - WebSocket - Sensor - Signal Processing - Linux Systems ### Nice to have - Dify - MCP - Chat platform API integration - HID protocols - Peripheral MCU communication - Embedded display integration - Web-based companion app configuration UIs - OTA firmware distribution - Chinese language proficiency --- Source: [Apply at logitech.wd5.myworkdayjobs.com](https://logitech.wd5.myworkdayjobs.com/en-US/Logitech/job/Suzhou-China/Lead-Embedded-Software-Engineer_146647-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)