Lead Agentic AI Solutions for Wealth Management

Third Nexus Group Limited

Greater London

On-site

GBP 60,000 - 100,000

Full time

14 days+
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Job summary

Third Nexus Group Limited in London seeks an AI Solutions Lead to drive discovery, design, and deployment of agentic AI workflows across front-to-back business functions within a highly regulated wealth management environment.

The role requires owning AI use cases end-to-end, designing robust AI agents, and ensuring governance and ROI. Strong English communication and stakeholder engagement are essential; experience with LLM workflows and RAG is highly valued.

Qualifications

  • Hands-on experience designing and implementing LLM-driven workflows.
  • Experience with agentic tool orchestration and RAG.
  • Experience evaluating AI outputs with guardrails and human-in-the-loop.
  • Ability to bridge commercial stakeholders and technical teams.
  • Excellent communication in English; additional languages a plus.

Responsibilities

  • Collaborate with business heads to identify AI opportunities.
  • Own AI use cases from framing to production rollout.
  • Design and deploy AI agents and workflows aligned with compliance.
  • Facilitate discovery workshops and translate business challenges into specs.
  • Monitor performance, ROI, and establish guardrails across the firm.

Skills

LLM-driven workflows
Agentic tool orchestration
RAG (retrieval-augmented generation)
Human-in-the-loop controls
Stakeholder management

Education

Degree in Computer Science
Data Science
Engineering
Business Informatics
Finance
Equivalent practical experience

Job description

Third Nexus Group Limited in London seeks an AI Solutions Lead to drive discovery, design, and deployment of agentic AI workflows across front-to-back business functions within a highly regulated wealth management environment.

The role requires owning AI use cases end-to-end, designing robust AI agents, and ensuring governance and ROI. Strong English communication and stakeholder engagement are essential; experience with LLM workflows and RAG is highly valued.

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