At a Glance
- Tasks: Design and build scalable AI architectures for enterprise-level projects.
- Company: Leading consulting and technology organisation transforming financial services with AI.
- Benefits: Hybrid work model, 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 environments.
- Qualifications: Experience in AI/ML, cloud platforms, and strong communication skills required.
The predicted salary is between 80000 - 100000 £ 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
Technical Skills:
- Python
- LLMs, prompt engineering, fine-tuning, RAG
- LangChain, LangGraph, Agent frameworks
- Vector databases and semantic search
- MLOps and LLMOps
- Containerisation, Kubernetes and GPU infrastructure
Requirements:
- 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.
Enterprise AI Architect - Scalable GenAI & LLM Platforms employer: Datatech Analytics
As a leading consulting and technology organisation, we pride ourselves on fostering a dynamic work culture that champions innovation and collaboration. Our hybrid work model allows for flexibility while providing ample opportunities for professional growth in the rapidly evolving field of AI, particularly within the Financial Services sector. Join us to be part of transformative projects that not only enhance your skills but also contribute to meaningful advancements in enterprise AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Enterprise AI Architect - Scalable GenAI & LLM Platforms
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to AI architecture and deployment. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge around LLMs, prompt engineering, and scalable AI platforms. We want you to feel confident discussing your experience and how it aligns with the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Enterprise AI Architect - Scalable GenAI & LLM Platforms
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Enterprise AI Architect role. Highlight your experience with scalable AI architectures and any relevant projects you've worked on in financial services.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and how your background makes you a great fit for this position. Be specific about your experience with LLMs and cloud platforms, and don’t forget to mention your stakeholder engagement skills!
Showcase Your Technical Skills:In your application, be sure to highlight your technical expertise, especially in Python, MLOps, and containerisation. We want to see how you’ve applied these skills in real-world scenarios, so don’t hold back!
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 shows us you’re keen to join our team!
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, especially in the context of financial services. Brush up on your knowledge of LLMs, prompt engineering, and how to transition from proof of concept to production-grade deployment.
✨Showcase Your Technical Skills
Be ready to discuss your experience with Python, MLOps, and containerisation technologies like Kubernetes. Prepare examples of how you've built or supported AI platforms, and be specific about the tools and frameworks you've used.
✨Engage with Stakeholders
Demonstrate your strong communication skills by discussing how you’ve collaborated with various teams in past projects. Highlight your ability to advise clients on AI platform capabilities and implementation strategies, as this is crucial for the role.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about challenges you've faced in AI deployment and how you overcame them, particularly in regulated environments like financial services.
