Agentic AI Engineer | Durlston Partners | UAE

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Job Title:

Agentic AI Engineer | Durlston Partners | Abu Dhabi, UAE

🏢 Recruiting Company:
Durlston Partners

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Job Location:

Abu Dhabi, United Arab Emirates

💼 Job Type: Full-Time, Onsite (Relocation Supported)

📧 Application Method:

📌 Compensation: USD 100,000 – 200,000

📌 Additional Info:
Elite AI Quant Team | High-Compute Environment | No Finance Background Required

The Agentic AI Engineer will design, build, and scale next-generation autonomous AI systems powering high-performance research and trading platforms. This role is central to advancing multi-agent architectures, reasoning-based agents, and cutting-edge experimentation within a world-class AI engineering team in Abu Dhabi.

In this role, you will join a deeply technical, high-impact AI Quant group focused on building foundational agentic systems from the ground up. You will work with large foundation models, structured multi-agent orchestration frameworks, and advanced experimentation pipelines to push the boundaries of autonomous AI. Your work will directly influence large-scale research and production environments, supported by a flat team structure and extensive compute resources.

Beyond model development, you will help architect end-to-end frameworks, optimize distributed workloads, and drive innovation in agent behavior, reasoning, and coordination for complex real‑world workflows.

• Build and scale agentic AI systems leveraging LLMs, ReAct-style agents, and multi-agent orchestration frameworks.
• Develop Python-based infrastructure for experimentation, training, and deployment in Linux environments.
• Implement distributed, multi-GPU training pipelines and high-throughput experimentation workflows.
• Architect autonomous multi-agent frameworks for research, data processing, and decision-making tasks.
• Collaborate closely with quant researchers and AI engineers on cutting-edge model development.
• Optimize performance, reliability, and scalability across AI systems and compute environments.

• Hands‑on experience working with LLMs and foundation model‑based systems.
• Strong Python engineering skills in Linux‑based environments.
• Experience with multi‑agent systems, agent reasoning, or autonomous agent frameworks (e.g., Lang Chain, Lang Graph, ReAct).
• Background in distributed training, multi‑GPU systems, or large‑scale experimentation.
• Strong interest in agentic AI, research automation, and high‑performance engineering.
• Ability to work in a fast‑paced, ownership‑driven environment.

• Exposure to reinforcement learning or decision‑making frameworks.
• Experience building ML infrastructure, pipelines, or deployment tooling.
• Familiarity with HPC clusters, cloud compute scaling, or model parallelism.
• Understanding of prompt engineering or model alignment workflows.

Demonstrate concrete hands‑on examples of agentic system builds—such as multi‑agent orchestration, autonomous workflows, or distributed experimentation—as real‑world engineering depth in this niche is the strongest differentiator for elite AI Quant roles.