At a Glance
- Tasks: Design and build scalable AI architectures for financial services.
- Company: Leading consulting and technology firm transforming AI in banking.
- Benefits: Hybrid work, competitive salary, and opportunities for professional growth.
- Other info: Open to various experience levels, from Manager to Associate Director.
- Why this job: Join a team shaping the future of AI in finance and make a real impact.
- Qualifications: Experience in AI architecture and strong communication skills required.
The predicted salary is between 70000 - 90000 € per year.
We're supporting a major consulting and technology organisation delivering enterprise AI and data transformation programmes across Financial Services. The focus is designing scalable AI architectures that move beyond proof of concept into secure, production-grade deployment across banking environments. Hiring across multiple levels, from Solution Architects through to senior technical leadership.
What you'll be doing:
- Designing AI and GenAI architecture strategies and roadmaps
- Building scalable AI/ML and Agentic AI platforms
- Working across LLMs, RAG, embeddings and semantic search
- Supporting AI deployment, governance and integration patterns
- Collaborating with engineering, data, DevOps and business teams
- Advising clients on AI platform capability and implementation strategy
Environment:
- Python
- LLMs, prompt engineering, fine-tuning, RAG
- LangChain, LangGraph, Agent frameworks
- Vector databases and semantic search
- MLOps and LLMOps
- AWS, Azure, GCP, Databricks
- Containerisation, Kubernetes and GPU infrastructure
Requirements:
- Experience designing enterprise AI or ML architectures
- Strong understanding of cloud and modern data platforms
- Exposure to scalable AI deployment and integration patterns
- Financial Services or regulated industry experience essential
- Strong stakeholder engagement and communication skills
- Open to candidates from Manager through to Associate Director level.
If you're open to a confidential conversation about the AI architecture market, please message me directly.
Locations
AI Solution Architect - Financial Services Consulting in Edinburgh, Scotland employer: Datatech Analytics
As a leading consulting and technology organisation in Scotland, we pride ourselves on fostering a dynamic work culture that champions innovation and collaboration. Our employees benefit from a hybrid working model, competitive remuneration, and extensive opportunities for professional growth within the rapidly evolving field of AI and financial services. Join us to be part of transformative projects that not only enhance your skills but also contribute to the future of banking technology.
StudySmarter Expert Advice🤫
We think this is how you could land AI Solution Architect - Financial Services Consulting in Edinburgh, Scotland
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in AI and financial services. Use platforms like LinkedIn to connect and engage with them; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your AI projects, especially those related to scalable architectures or financial services. This gives potential employers a taste of what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with cloud platforms, MLOps, and stakeholder engagement. Practice common interview questions and scenarios relevant to AI architecture.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications that way!
We think you need these skills to ace AI Solution Architect - Financial Services Consulting in Edinburgh, Scotland
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the job description. Highlight your experience with AI architectures and any relevant projects you've worked on in financial services. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a perfect fit for the role. Don’t forget to mention specific technologies or methodologies you’ve used that relate to our needs.
Showcase Your Technical Skills:When listing your skills, be specific! Mention your experience with Python, LLMs, and any cloud platforms like AWS or Azure. We love seeing candidates who can demonstrate their technical prowess clearly and confidently.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Datatech Analytics
✨Know Your AI Architecture Inside Out
Make sure you’re well-versed in designing scalable AI architectures. Brush up on your knowledge of LLMs, RAG, and the latest trends in AI deployment. Being able to discuss specific examples from your experience will show that you’re not just familiar with the concepts but can apply them effectively.
✨Showcase Your Cloud Expertise
Since the role involves working with cloud platforms like AWS, Azure, and GCP, be prepared to discuss your experience with these technologies. Highlight any projects where you’ve implemented AI solutions in a cloud environment, focusing on how you tackled challenges and ensured scalability.
✨Engage with Stakeholders
Strong communication skills are key for this role. Think about times when you’ve successfully engaged with stakeholders or collaborated with cross-functional teams. Be ready to share how you’ve navigated complex discussions and driven consensus on AI strategies.
✨Prepare for Technical Questions
Expect technical questions related to MLOps, containerisation, and GPU infrastructure. Brush up on your knowledge of these areas and be ready to explain your thought process in solving technical problems. Practising with mock interviews can help you articulate your answers clearly.
