Quant LLM Engineer

About the Venture

An established debt and M&A advisory boutique with offices in London and Dubai (DIFC) is building a new AI-first systematic trading business. The team is creating a platform from scratch that uses large language models and machine learning for research, signal generation, and execution.

This is a small founding group of three people: the CEO, one AI engineer, and this role.

Role Overview

The position is for a founding Quant AI Engineer who will own the full quantitative workflow end to end, including research, backtesting, and production rollout. You will work directly with the CEO, allowing ideas to move from concept to live capital within days rather than months.

Key Responsibilities

You will be expected to build and refine trading systems, develop AI-based research processes, and help define the technical direction and operating culture of the new business.

What You Need to Bring

The ideal candidate has a strong quantitative background, practical trading strategy experience, advanced Python skills, and direct exposure to LLM-based workflows in research or trading. The role also suits someone comfortable with early-stage ownership and high-upside compensation.

Compensation and Advantages

The opportunity includes an uncapped performance bonus linked to strategy profitability, support from a revenue-generating advisory firm, direct access to leadership, and a Dubai/DIFC base with 0% personal income tax.

Additional Notes

This is a founding-role environment with significant influence over what gets built. It is positioned as an alternative to a traditional fund seat, especially for someone who wants direct participation in the upside created by their work.

Responsibilities

• Develop, test, and improve AI-native and systematic trading ideas across algorithmic, hedge fund, and long-only investment styles.
• Create LLM-enabled research workflows that can pull useful signals from unstructured sources such as filings, news, transcripts, and alternative data.
• Move models from experimentation into reliable production systems with monitoring and live deployment.
• Help establish the architecture, tooling, and working culture of the trading operation from the ground up.

Requirements

• Strong grounding in mathematics, statistics, or another quantitative discipline; a Master’s degree or PhD is considered an advantage.
• 3 to 6 years of experience building and backtesting trading strategies, whether at a fund, prop shop, or as an independent with a verifiable record.
• Strong Python programming ability and comfort taking ownership of a codebase end to end.
• Practical experience using LLMs in research, analytics, or trading applications, including RAG, fine-tuning, or agent-based pipelines.
• Genuine interest in early-stage ownership and performance-linked upside.

Perks

• Uncapped bonus potential tied directly to strategy P&L.
• Opportunity to operate with the backing of an established, revenue-producing advisory business.
• Direct communication with the CEO and minimal organizational layers.
• Dubai/DIFC location with 0% personal income tax.
• Influence over the team, tooling, and long-term direction from day one.

Eligibility

Applicants should be experienced quantitative professionals or serious independent traders with a proven track record, and should be ready to take ownership in an early-stage trading venture.

Why This Role

For someone whose alpha has previously supported someone else’s bonus pool, this role offers a chance to sit on the other side of that arrangement and share directly in the upside.

Location

Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates. The venture is also described as being based in Dubai (DIFC).