Wealth AI Solutions Engineer: RAG & LLM Apps

Rothstein Recruitment Ltd; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Rothstein Recruitment Ltd is seeking an AI Solutions Engineer to shape the use of Generative AI across a wealth-management environment. You will translate business challenges into production AI solutions using Python, RAG, LLMs and agentic workflows, collaborating with business users across IT, Data, Risk and Compliance.

You will prototype rapidly, then mature successful solutions with robust logging, testing and governance, ensuring secure data handling and compliant AI practices.

Qualifications

• 3+ years in software or AI engineering with hands-on generative AI.
• Strong Python development and testing fundamentals.
• Experience building agentic AI workflows and RAG solutions.

Responsibilities

• Build, test, deploy and maintain Generative and Agentic AI applications per architecture and governance standards.
• Collaborate with users and SMEs to understand workflows and refine acceptance criteria.
• Develop agents and multi-step AI workflows using model APIs, tool calling and memory.
• Build RAG and knowledge solutions including document ingestion, embeddings, search and grounding.
• Integrate AI solutions with internal systems via Python and APIs.
• Create and maintain automated tests and AI evaluation sets for groundedness and relevance.
• Apply secure development practices and maintain logging, monitoring and documentation.

Skills

Python

LLMs

Generative AI

Agentic AI

RAG

REST APIs

Git

CI/CD

Azure

Agile

Security

Tools

LangChain

Docker

FastAPI

Kubernetes

OpenAI API

Azure

GitHub Copilot

LLM Frameworks

Job description

Rothstein Recruitment Ltd is seeking an AI Solutions Engineer to shape the use of Generative AI across a wealth-management environment. You will translate business challenges into production AI solutions using Python, RAG, LLMs and agentic workflows, collaborating with business users across IT, Data, Risk and Compliance.

You will prototype rapidly, then mature successful solutions with robust logging, testing and governance, ensuring secure data handling and compliant AI practices.