At a Glance
- Tasks: Design and deploy AI systems for major banks, transforming their operations with cutting-edge technology.
- Company: Leading professional services organisation focused on AI transformation in banking.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic environment with leadership opportunities and mentorship for junior engineers.
- Why this job: Join a high-performing team and make a real impact in the financial services sector.
- Qualifications: Strong software engineering skills, experience with AI/ML systems, and a collaborative mindset.
The predicted salary is between 55000 - 75000 € per year.
A leading professional services organisation is seeking Senior Consultants and Managers – AI Engineers to join its AI & Data Financial Services practice, focused exclusively on AI transformation within Banking. This role sits within a high-performing engineering and delivery team helping major banks design, build, and scale AI-powered systems, agentic applications, and modern data platforms.
You will work across the full lifecycle of AI delivery, from architecture and rapid prototyping through to production deployment and operationalisation of GenAI solutions supporting the modernisation of core banking systems through advanced machine learning and generative AI. The role blends hands-on engineering, solution design, and client-facing delivery, with increasing leadership responsibility at Manager level.
Key Responsibilities- Translate banking client requirements into AI architecture strategies and delivery roadmaps
- Design, build, and deploy AI systems, including GenAI and agent-based applications
- Deliver rapid prototypes to validate technical and business use cases
- Build and maintain production-grade AI services and APIs (e.g. FastAPI or similar)
- Collaborate with engineers, data scientists, architects, and business stakeholders to deliver end-to-end solutions
- Evaluate and implement AI technologies across open-source and commercial ecosystems
- Design integration patterns for enterprise banking environments
- Contribute to system architecture, design decisions, and technical documentation
- Support architecture governance, reviews, and design approvals
- Ensure solutions meet security, risk, and regulatory requirements
- Contribute to business cases, ROI analysis, and client proposals
- Engage directly with client stakeholders across technical and business teams
- Mentor junior engineers and support capability development within the team (Manager level)
- Strong background in software engineering or data engineering with applied AI (Python, SQL)
- Experience delivering AI/ML or generative AI systems in production
- Strong understanding of LLMs, including: Retrieval-Augmented Generation (RAG)
- Experience building or delivering agentic AI systems
- Strong Python engineering skills and experience building API-based services
- Experience with modern data architectures and system design
- Experience working in cloud environments (AWS, Azure, GCP, or Databricks)
- Familiarity with CI/CD pipelines and modern engineering practices
- Experience with vector databases (e.g. Pinecone, Chroma)
- Experience with agent frameworks (e.g. LangChain, LangGraph, or similar)
- Understanding of AI evaluation frameworks and production readiness
- Experience working in Agile delivery environments (Agile, SAFe, XP, Jira, Confluence, etc.)
- Experience in Banking (essential focus area)
- Exposure to Model Context Protocol (MCP)
- Experience in regulated enterprise environments
- Understanding of MLOps / LLMOps practices
- Ability to contribute to ROI modelling, business cases, and AI value articulation
- Experience mentoring or leading delivery teams (Manager level)
- Senior Consultant – AI Engineer: Hands-on delivery of AI systems and prototypes, strong focus on engineering execution and solution build, supports architecture and design decisions, contributes to client delivery and documentation, works closely with senior engineers and stakeholders.
- Manager – AI Engineer: Leads small technical squads and delivery workstreams, owns end-to-end delivery of AI solutions, makes architectural and technical decisions, leads client stakeholder engagement, supports estimation, planning, and ROI modelling, mentors and develops team members.
Artificial Intelligence Engineering Consultant in London employer: MBN Solutions
As a leading professional services organisation, we pride ourselves on fostering a dynamic and inclusive work culture that champions innovation and collaboration. Our London-based AI & Data Financial Services practice offers exceptional growth opportunities for AI Engineering Consultants, with access to cutting-edge technology and the chance to work alongside industry experts on transformative projects within the banking sector. We provide competitive salaries, comprehensive benefits, and a hybrid working model that promotes work-life balance, making us an excellent employer for those seeking meaningful and rewarding careers in AI.
StudySmarter Expert Advice🤫
We think this is how you could land Artificial Intelligence Engineering Consultant in London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the banking and AI sectors. Attend meetups, webinars, or industry events to meet potential employers and learn about job openings that might not be advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those related to banking transformation. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with Python, SQL, and AI systems, and how you've tackled challenges in previous roles.
✨Tip Number 4
Don't forget to apply through our website! We have loads of opportunities that might be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Artificial Intelligence Engineering Consultant in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of AI Engineering Consultant. Highlight your experience with AI systems, Python, and any relevant banking projects. We want to see how your skills match 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 in banking and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love a good story!
Showcase Your Projects:If you've worked on any AI or machine learning projects, make sure to showcase them. Whether it's a prototype or a full deployment, we want to see your hands-on experience and how you've tackled challenges in the past.
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 MBN Solutions
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI systems, especially generative AI and LLMs. Be ready to discuss your experience with Python, SQL, and any relevant frameworks like LangChain or Pinecone. The more specific examples you can provide about your past projects, the better!
✨Understand the Banking Sector
Since this role is focused on banking transformation, it’s crucial to understand the unique challenges and requirements of the financial services industry. Familiarise yourself with current trends in banking technology and be prepared to discuss how AI can address these challenges.
✨Showcase Your Collaboration Skills
This position involves working closely with engineers, data scientists, and business stakeholders. Be ready to share examples of how you've successfully collaborated in the past, particularly in Agile environments. Highlight your ability to communicate complex technical concepts to non-technical stakeholders.
✨Prepare for Technical Questions
Expect to face technical questions that assess your problem-solving skills and understanding of AI architecture. Practice explaining your thought process when designing AI solutions and be prepared to tackle hypothetical scenarios related to system design and deployment.
