At a Glance
- Tasks: Design and build scalable AI architectures for financial services.
- Company: Leading consulting and technology firm transforming AI in finance.
- 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 dynamic team shaping the future of AI in banking.
- 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.
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.
AI Solution Architect - Financial Service Consulting employer: Datatech Analytics
As a leading consulting and technology organisation, we pride ourselves on fostering a dynamic work culture that encourages innovation and collaboration. Our London-based team enjoys hybrid working arrangements, competitive benefits, and ample opportunities for professional growth in the rapidly evolving field of AI within 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 Service Consulting
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in AI and Financial Services. Attend meetups or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI architecture projects, especially those relevant to financial services. This could be anything from case studies to GitHub repositories. When you can demonstrate your expertise, it makes you stand out in a crowded field.
✨Tip Number 3
Prepare for interviews by brushing up on common AI and ML concepts, especially those mentioned in the job description. Be ready to discuss your experience with cloud platforms and scalable deployments. Practising with mock interviews can help you feel more confident when the real deal comes around.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers. So, get your application in and let’s make some AI magic happen!
We think you need these skills to ace AI Solution Architect - Financial Service Consulting
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the AI Solution Architect role. Highlight your experience in designing scalable AI architectures and any relevant projects you've worked on in the financial services sector.
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 our team. Don’t forget to mention specific technologies or methodologies you’ve used that relate to the job description.
Showcase Your Technical Skills:In your application, be sure to highlight your technical expertise, especially in Python, cloud platforms, and AI deployment strategies. We want to see how you can contribute to building scalable AI/ML platforms and integrating them into banking environments.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values!
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 semantic search, as these are key components for the role. Be ready to discuss how you've applied these technologies in past projects.
✨Showcase Your Cloud Expertise
Since cloud platforms like AWS, Azure, and GCP are crucial for this position, highlight your experience with them. Prepare examples of how you've leveraged these platforms for AI deployment and integration, especially in financial services.
✨Engage with Stakeholders
Strong communication skills are a must! Think of instances where you’ve successfully engaged with stakeholders to drive AI initiatives. Be prepared to share how you’ve navigated complex discussions and aligned technical solutions with business needs.
✨Demonstrate Team Collaboration
This role involves working closely with engineering, data, and DevOps teams. Have examples ready that illustrate your collaborative approach. Discuss how you’ve contributed to cross-functional teams and the impact it had on project success.
