Senior AI Systems & Local LLM Engineer (Smart Home & Agentic AI)

The client is a Dubai-based real estate and hospitality developer creating technology-led, wellness-focused living environments. It brings together design, engineering and artificial intelligence to deliver smart, future-ready communities. Its teams work at the intersection of property, technology and longevity. The client is now expanding its technology organisation to build proprietary AI and smart-living capabilities.

We are seeking a versatile Senior AI Systems & Local LLM Engineer who bridges the gap between state-of-the-art frontier models, smart home automation systems, and self-hosted, local LLM infrastructure. You will architect, deploy, and scale local inference engines, real-time voice and avatar agents, and complex agentic workflows, while maintaining full ownership over our virtualized infrastructure and IoT setups.

If you thrive on rapid prototyping (“vibe coding” with high velocity), love running local hardware and virtualized environments, and prefer pragmatism over slow-moving bureaucracy, this role is for you.

• →Local LLM & Inference Orchestration: Deploy, tune, and maintain self-hosted LLM setups using tools like LMStudio, Exo, vLLM, and Ollama. Integrate locally trained/fine-tuned weights into production environments.
• →Agentic Workflows & Avatars: Design and wire up autonomous AI agents using frameworks like OpenClaw, Hermes, and custom agentic graphs. Build real-time voice agents and interactive AI avatars for seamless human-computer interaction.
• →Smart Home & Voice Integration: Integrate local AI voice agents and agentic control layers directly into Home Assistant for low-latency, privacy-focused automation and interactive control.
• →Hybrid Model Routing: Build resilient middleware that routes queries dynamically between high-throughput local models and top-tier frontier APIs (OpenAI, Anthropic, Gemini).
• →Infrastructure & Virtualization: Provision, manage, and optimize enterprise compute nodes using Linux (Ubuntu/Debian) and Proxmox VE. Handle GPU passthrough, container orchestration, and resource allocation.
• →Full-Stack AI Integration: Develop high-concurrency backend services, real-time streaming endpoints (WebSockets/SSE), and API layers using Python (FastAPI/AsyncIO) and Node.js.

• Experience: 3-5 years of software or AI engineering experience with a strong portfolio of deployed production systems.
• Home Assistant Mastery: Hands-on experience integrating custom components, local voice pipelines, or LLMs into Home Assistant.
• Rapid Development (“Vibe Coding”): Exceptional speed and fluency leveraging modern AI-assisted coding tools (Cursor, Copilot, Windsurf) to write clean, working code quickly.
• Systems & Virtualization: Comfort operating in raw Linux environments, managing Proxmox hypervisors, and configuring LXCs/VMs for GPU workloads and smart home services.
• Language Proficiency: Strong, production-grade skills in Python and Node.js.
• Local AI Ecosystem: Hands-on experience with local model deployment, quantization formats (GGUF, EXL2, AWQ), and multi-device local compute clusters (Exo/LMStudio).
• Agentic Frameworks: Familiarity with agent orchestration paradigms, tool use, local memory storage, and frameworks like Hermes or OpenClaw.

• Experience with IoT communication protocols like MQTT, Matter, and Zigbee (Zigbee2MQTT / ZHA).
• Experience fine-tuning local models (Unsloth, QLoRA, Axolotl).
• Familiarity with real-time audio pipeline tools (WebRTC, Deepgram, ElevenLabs) and local TTS/STT stacks such as Whisper, Piper, and XTTS.
• Active homelabber or self-hosting enthusiast with real-world experience managing physical/virtual GPU rigs and smart home setups.

• Inference & Orchestration: LMStudio, Exo, vLLM, Ollama, OpenClaw, Hermes
• Virtualization & OS: Proxmox VE, Linux (Debian/Ubuntu), Docker, LXC, GPU Passthrough
• Smart Home & IoT: Home Assistant, MQTT, Matter, Zigbee
• Backend Development: Python (FastAPI, AsyncIO), Node.js, WebSockets / SSE
• Frontier APIs: OpenAI, Anthropic, Gemini