Production AI Engineer: LLM & Agentic Systems for Finance

Bowden Brown; Greater London; On-site; GBP 120,000 - 190,000; Full time

Job summary

Bowden Brown is sourcing an AI Engineer for a leading global investment firm to design and deliver applied AI systems that impact research, trading, and business decisions.

You will work with Portfolio Managers, quants, and senior leadership to architect production-grade LLM systems and agentic AI across the firm, shipping tools integrated into investment workflows and securely connecting to enterprise data.

Qualifications

• 4+ years of industry experience with the last 2+ years building and deploying production AI systems.
• Advanced degree (MS or PhD) in Computer Science, AI, ML, or related quantitative field.
• Hands-on experience with production LLM applications including evaluation, monitoring, and iteration.
• Strong experience with agentic frameworks and agent design patterns.

Responsibilities

• Define and execute the technical roadmap for firmwide AI initiatives.
• Design, build, and deploy LLM-powered tools embedded directly into investment workflows.
• Architect agentic systems capable of multi-step reasoning, planning, and tool execution.
• Build and operate MCP servers to securely connect AI agents to enterprise data and APIs.
• Own the full LLM lifecycle including prompt and system design, model selection, evaluation, deployment, monitoring, and iteration.
• Lead rapid prototyping using RAG, tool and function calling, and modern agent frameworks.
• Establish best practices for responsible, production-grade AI deployment.
• Mentor engineers and help raise the technical bar across applied AI initiatives.

Skills

Production AI systems

Python engineering

Agent frameworks

REST APIs

Education

MS or PhD in CS/AI/ML

Tools

MCP servers

Agent frameworks

Job description

Bowden Brown is sourcing an AI Engineer for a leading global investment firm to design and deliver applied AI systems that impact research, trading, and business decisions.

You will work with Portfolio Managers, quants, and senior leadership to architect production-grade LLM systems and agentic AI across the firm, shipping tools integrated into investment workflows and securely connecting to enterprise data.