AI Engineer

Durlston Partners; Abu Dhabi; On-site; AED 700,000 - 1,000,000; Full time

Benefits offered by this job

Visa sponsorship

Relocation package

Private health insurance

Dependent schooling allowances

Job summary

Durlston Partners in Abu Dhabi seeks a senior AI systems engineer to architect multi-agent orchestration, robust tool-use, and production-grade agentic infrastructure. You will design scalable task decomposition, inter-agent communication, and state management for autonomous workflows.

Bring deep expertise in LLMs, RAG, agent frameworks, and high-throughput engineering. The role includes a tax-free base salary, discretionary bonus, visa sponsorship, relocation, private health insurance, and

Qualifications

• Deep expertise building with advanced LLM architectures, RAG, agentic reasoning, and multi-agent workflows.
• Clear grasp of where standard agent frameworks break down, and how to engineer resilient workarounds.
• Background in financial services, investment management, fintech, or high-throughput engineering environments (advantageous).
• Active open-source contributions, AI research publications, or relevant patents are highly valued.
• LangGraph, AutoGen, or custom agent frameworks.

Responsibilities

• Design and build scalable systems for task decomposition, inter-agent communication, and state management.
• Own sandboxing, guardrails, automated retries, fallback logic, and real-time observability.
• Build rigorous evaluation pipelines to catch performance regressions before production deployment.
• Architect reliable retrieval (RAG) and tool-use infrastructure across structured and unstructured data sources.

Skills

LLM architectures

RAG pipelines

Multi-agent systems

Agent frameworks

Python

AsyncIO

Production engineering

Tools

LangGraph

AutoGen

custom agent frameworks

Job description

A private investment office in Abu Dhabi is expanding its elite technical team to build and own state-of-the-art multi-agent orchestration and agentic infrastructure. You will architect the core systems that enable autonomous AI agents to plan, execute tool calls, retry on failure, and reliably hand off complex workflows in production.

Key Responsibilities

• Design and build scalable systems for task decomposition, inter-agent communication, and state management.
• Own sandboxing, guardrails, automated retries, fallback logic, and real-time observability.
• Build rigorous evaluation pipelines to catch performance regressions before production deployment.
• Architect reliable retrieval (RAG) and tool-use infrastructure across structured and unstructured data sources.

What You Bring

• Deep expertise building with advanced LLM architectures, RAG, agentic reasoning, and multi-agent workflows.
• A clear grasp of where standard agent frameworks (e.g., standard ReAct loops) break down, and how to engineer resilient workarounds.
• Background in financial services, investment management, fintech, or high-throughput engineering environments (advantageous).
• Active open-source contributions, AI research publications, or relevant patents are highly valued.
• LangGraph, AutoGen, or custom agent frameworks
• Python (PyTorch/TensorFlow, AsyncIO, FastAPI)
• Highly competitive, tax-free base salary
• Discretionary performance-based annual bonus
• Full visa sponsorship and premium relocation package
• Comprehensive private health insurance and dependent schooling allowances