Lead Embedded Software Engineer

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
• 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

Requirements

• 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
• 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

Benefits

Additional Information

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way. Department: C4C HW Engineering Role Summary 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.

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at logitech? Share your experience