AI Engineer (Lead/Senior/Junior) - Large Language Models and Vision-Language Models

Job Title: AI Engineer (roles from Lead, Senior and Junior)

Location: Abu Dhabi (Relocation is required)

Salary: €85,000 - €115,000 (Tax Free + amazing Relocation benefits and healthcare + 40 days holiday including Public holidays + Free Lunch

My client is evolving and looking for talent with a deep understanding of Large Language Models (LLMs), Vision-Language Models (VLMs) and agentic model architectures. The ideal candidate will have strong foundation in both research and engineering, with hands on experience developing, fine tuning and deploying AI systems.

The candidate will contribute to building scalable, production ready AI applications, integrating multimodal reasoning, and pushing the boundaries of autonomous intelligent agents.

Key Responsibilities

• Design, train, fine-tune, and optimize LLMs and VLMs for real-world
• Develop and orchestrate autonomous agent frameworks capable of multi-step reasoning, planning, and tool use.
• Build scalable, low-latency inference systems for large models using frameworks like DeepSpeed, vLLM, TensorRT, or ONNX Runtime.
• Implement distributed training, model parallelism, and efficient inference pipelines; also optimize deployment for edge devices, GPUs, and cloud-based platforms.
• Research & Innovation: Stay up to date with the latest advancements in LLMs, multimodal models, and autonomous agents.

Key Skills

• Strong understanding of LLMs, VLMs, transformers, and multimodal architectures.
• Experience with fine-tuning, LoRA/QLoRA, quantization, distillation, and evaluation.
• Knowledge of neurosymbolic methodology
• Knowledge of reinforcement learning (RLHF, RLAIF) and alignment techniques.
• Experience with frameworks such as LangChain, LlamaIndex, AutoGPT, CrewAI, OpenAI Agents, Hugging Face Transformers/Agents.
• Ability to design reasoning loops, memory systems, and multi-agent coordination.
• Proficient in PyTorch, TensorFlow, Hugging Face, OpenAI APIs, DeepSpeed, vLLM
• Knowledge with Weaviate, Pinecone, FAISS, Milvus (vector databases), Redis, Kafka.
• Knowledge with Weights & Biases, MLflow, TensorBoard, Evals frameworks.
• Python for AI research, prototyping, and deployment pipelines.
• C++for performance-critical components, model inference optimization, and system integration.
• Proficiency with Docker, and AI distributed training systems.
• Strong knowledge of CUDA, GPU optimization, and high-performance computing.
• Familiarity with cloud platforms (AWS, GCP, Azure) and edge deployment strategies.

Qualifications

• Master’s, or PhD in Computer Science, AI/ML, Robotics, or related field.
• Proven track record of hands-on work with LLMs, VLMs, or agentic frameworks.
• Experience in productionizing AI systems at scale.
• Excellent communication and collaboration skills.