Front-Office AI Engineer for Macro & Fixed Income

eFinancialCareers

Greater London

On-site

GBP 120,000 - 180,000

Full time

6 days ago
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Job summary

A London-based hedge fund seeks an AI Engineer to build and embed production-grade AI solutions across Macro and Fixed Income investment workflows. You will collaborate with portfolio managers, analysts and traders, while aligning with central AI and Data Science teams to deliver scalable products.

Responsibilities include deploying LLMs, agentic AI, and data-driven tools for research, pricing, risk and trading, translating requirements into robust products, and driving desk adoption through

Qualifications

  • Experience supporting front-office users of Macro or Fixed Income markets.
  • 2+ years of professional software engineering, quantitative development or applied AI experience.
  • Strong Python engineering skills and production-grade AI applications.
  • Exposure to LLM apps, RAG, AI agents, monitoring or model integration in production environments.
  • Strong communication with technical teams and investment professionals.

Responsibilities

  • Identify high-value AI opportunities with Macro and Fixed Income investment teams.
  • Build and deploy production-grade AI and data-driven applications for research, pricing, risk and trading workflows.
  • Translate requirements from traders and analysts into robust technical products that can be iterated quickly.
  • Drive adoption through on-desk demonstrations, collaboration and user education.
  • Capture feedback from investment users and influence the internal AI platform development.

Skills

Python
AI deployment
Stakeholder communication
Front-office collaboration

Tools

LLM frameworks

Job description

A London-based hedge fund seeks an AI Engineer to build and embed production-grade AI solutions across Macro and Fixed Income investment workflows. You will collaborate with portfolio managers, analysts and traders, while aligning with central AI and Data Science teams to deliver scalable products.

Responsibilities include deploying LLMs, agentic AI, and data-driven tools for research, pricing, risk and trading, translating requirements into robust products, and driving desk adoption through

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