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AI Solution Architect - Financial Services Consulting

Datatech AnalyticsEdinburgh, Scotland🇬🇧United KingdomPosted 1 Aug 2026

Why This Role Stands Out

You'll thrive as an AI Solution Architect in this hybrid role, designing cutting-edge AI architectures for major financial services transformations and gaining experience with leading-edge technologies. If you're a mid-senior AI/ML architect with a strong understanding of cloud platforms and financial services, this is your chance to make a significant impact and advance your career.

Quick Overview

Work Type
Hybrid
Schedule
Full Time
Level
Mid Senior

Job Description

AI Solution Architect - FS Consulting

Ready to take AI beyond proof of concept? A leading consulting and technology firm is hiring AI Solution Architects and Technical AI Leaders to shape enterprise AI and GenAI strategy for major banking clients, turning ambitious ideas into secure, production-grade deployments across regulated financial environments. Hybrid working, based in Scotland.

What you'll do
Set the AI and GenAI architecture strategy and roadmap. Build scalable AI/ML and Agentic AI platforms spanning LLMs, retrieval-augmented generation (RAG), embeddings and semantic search. Lead on deployment, governance and integration patterns, advise clients on platform capability and implementation strategy, and partner with engineering, data, DevOps and business teams to deliver end-to-end solutions.

Tech environment
Python, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure.

What we're looking for
Proven enterprise AI or ML architecture design, strong cloud and modern data platform knowledge, and demonstrable experience of scalable AI deployment and integration. Financial services or another regulated industry is essential, along with the stakeholder presence to advise at senior client level.

Applications welcomed from Manager through to Associate Director.


Skills

GCP
AWS
MLOps
Azure
Databricks
Kubernetes
Python

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