At a Glance
- Tasks: Build AI platforms and intelligent workflows in the financial services sector.
- Company: Major consulting and technology organisation leading AI transformation.
- Benefits: Hybrid work, competitive salary, and opportunities for professional growth.
- Other info: Open to all levels, from Engineers to Senior Managers.
- Why this job: Join a dynamic team and shape the future of AI in banking.
- Qualifications: Strong software or data engineering background with AI solution experience.
The predicted salary is between 60000 - 80000 € per year.
We're supporting a major consulting and technology organisation delivering AI and data transformation programmes across Financial Services and Banking. The focus is applied AI engineering, building production grade AI solutions across banking, risk, fraud, automation and enterprise platforms.
What you'll be doing:
- Building AI-enabled platforms and intelligent workflows
- Working with LLMs, RAG pipelines and embedding models
- Developing scalable backend services and AI integrations
- Collaborating across engineering, architecture and business teams
- Supporting AI deployment, governance and operational rollout
Environment:
- Python, SQL
- LLMs, prompt engineering, fine-tuning, RAG
- LangChain, LangGraph, Agent frameworks
- Vector databases, FastAPI, APIs
- AWS, Azure, GCP or Databricks
- CI/CD, MLOps and LLMOps
Requirements:
- Strong software or data engineering foundations
- Experience delivering AI or AI-enabled solutions
- Exposure to cloud and modern data platforms
- Financial Services or regulated industry experience essential
- Strong communication and stakeholder skills
Open to candidates from Engineer through to Senior Manager level.
AI Engineer - Financial Service Consulting 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 London-based team enjoys the benefits of hybrid working, competitive remuneration, and extensive 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 meaningful advancements in banking and risk management.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer - Financial Service Consulting
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with AI professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those related to financial services. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions and be ready to discuss your experience with Python, SQL, and cloud platforms like AWS or Azure.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace AI Engineer - Financial Service Consulting
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with AI engineering and financial services. We want to see how your skills align with the job description, so don’t be shy about showcasing relevant projects or technologies you've worked with!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI in financial services and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills:Since we're looking for someone with strong software and data engineering foundations, make sure to list your technical skills clearly. Mention your experience with Python, SQL, and any cloud platforms you've used. We want to know what tools you bring to the table!
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 on joining our team!
How to prepare for a job interview at Datatech Analytics
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI engineering, especially in the context of financial services. Be ready to discuss your experience with LLMs, RAG pipelines, and any relevant projects you've worked on. This will show that you understand the technical requirements and can hit the ground running.
✨Showcase Your Communication Skills
Since strong communication and stakeholder skills are essential for this role, prepare examples of how you've effectively collaborated with different teams. Think about times when you had to explain complex AI concepts to non-technical stakeholders – this will highlight your ability to bridge the gap between tech and business.
✨Familiarise Yourself with the Tools
Get comfortable with the tools mentioned in the job description, like Python, SQL, and cloud platforms such as AWS or Azure. If you have experience with CI/CD, MLOps, or vector databases, be ready to discuss how you've used these in past projects. This will demonstrate your hands-on experience and readiness for the role.
✨Prepare Questions About the Company
Have a few thoughtful questions ready about the company's approach to AI in financial services. This shows your genuine interest in their work and helps you assess if the company culture aligns with your values. Plus, it gives you a chance to engage in a meaningful conversation during the interview.
