AI Architect
Role Overview
Design, deploy, optimize, and scale production-grade AI solutions focused on conversational AI, agentic AI, LLM inference, and NVIDIA GPU infrastructure.
The role requires hands-on production implementation; general GenAI knowledge, prompt engineering, or DevOps experience alone is insufficient.
Key Skills for This Role
Full Job Posting
Position overview
Design, deploy, optimize, and scale production-grade AI solutions focused on conversational AI, agentic AI, LLM inference, and NVIDIA GPU infrastructure.
The role requires hands-on production implementation; general GenAI knowledge, prompt engineering, or DevOps experience alone is insufficient.
Location and work mode
- Based 100% onsite in Abu Dhabi, UAE.
- Immediate or short-notice joining is preferred.
Employment and compensation
- Full-time, long-term employment.
- Monthly salary is AED 20,000–22,000, depending on skills and experience.
- Benefits include UAE employment visa subject to requirements, medical insurance, applicable air ticket, and other standard employment benefits.
Key responsibilities
- Design conversational AI, agentic AI, and enterprise LLM solutions; develop voice agents, chatbots, and real-time STT/TTS systems.
- Build RAG pipelines and orchestration; deploy and optimize inference using vLLM, Hugging Face TGI, and TensorRT-LLM.
- Tune PagedAttention, KV cache, batching, GPU utilization, quantization, and distributed inference.
- Architect NVIDIA GPU infrastructure and deploy workloads on Kubernetes using GPU Operator and MIG.
- Support bare-metal clusters, scaling, production reliability, monitoring, observability, and troubleshooting.
- Collaborate with engineering and business teams to deliver secure, reliable production AI solutions.
Technical requirements
- Mandatory expertise includes conversational and agentic AI, voice agents, chatbots, STT/TTS, RAG, LLM orchestration, and production deployments.
- Required inference technologies include vLLM, Hugging Face TGI, TensorRT-LLM, PagedAttention, KV cache, continuous batching, FP8, INT4, AWQ, and GPTQ.
- Required GPU expertise includes NVIDIA H100, H200, and A100, distributed inference, tensor and pipeline parallelism, and GPU tuning.
- Required platform and monitoring skills include CUDA, Triton, FlashAttention, Kubernetes, NVIDIA GPU Operator, MIG, bare-metal clusters, Prometheus, Grafana, and DCGM.
Candidate eligibility
- At least five years of relevant hands-on technical experience and demonstrable production deployment and operation of AI/LLM solutions.
- Strong understanding of GPU-accelerated inference and performance optimization.
- Ten or more years is preferred for Senior/Lead Architect candidates.
- Candidates based in the UAE or India and immediate or short-notice joiners are preferred.
- Must meet applicable UAE work authorization, visa, and client deployment requirements.
Candidate submission and interview
- Submissions should include an updated CV highlighting AI/LLM implementations, current location, onsite willingness, salary details, notice period, and a summary of production experience.
- Include relevant projects involving vLLM, TensorRT-LLM, GPU optimization, or AI voice agents.
- The process includes technical screening and a detailed client interview; same-day technical interviews may be arranged.
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