At a Glance
- Tasks: Lead AI transformation projects in banking, designing and delivering scalable AI systems.
- Company: Top-tier professional services firm with a focus on innovation in financial services.
- Benefits: Competitive salary, hybrid work model, and extensive professional development opportunities.
- Other info: Opportunity for career growth in a collaborative and fast-paced environment.
- Why this job: Join a dynamic team at the forefront of AI technology and make a real impact.
- Qualifications: Strong background in software or data engineering with applied AI experience.
The predicted salary is between 80000 - 93000 € per year.
A leading professional services organisation is seeking a Senior Manager – AI Engineer to join its AI & Data Financial Services practice, focused on delivering large-scale AI transformation across Banking. This role sits at the forefront of enterprise AI engineering, architecture, and delivery leadership, helping major financial institutions design, build, and operate scalable AI systems that modernise core business processes.
You will operate across the full AI lifecycle—from strategy and architecture through to production deployment and optimisation of agentic AI systems—driving measurable business value through advanced machine learning and generative AI. This is a senior leadership role combining hands-on technical credibility with programme leadership, stakeholder influence, and team development.
Key Responsibilities- Translate senior stakeholder vision into AI transformation strategies, architecture, and delivery roadmaps.
- Lead and oversee multi-disciplinary AI engineering teams and workstreams.
- Design and deliver enterprise-scale AI systems, including agentic and GenAI solutions.
- Collaborate with architects, data scientists, DevOps, and business stakeholders to define end-to-end solutions.
- Evaluate and select AI technologies (open-source and commercial) and define enterprise deployment patterns.
- Lead design of API-based AI services and scalable backend systems (e.g. FastAPI).
- Ensure robust integration of AI systems into complex banking and capital markets environments.
- Establish and govern evaluation frameworks for AI and agent-based systems.
- Oversee CI/CD, MLOps, and LLMOps practices across delivery teams.
- Work closely with security, risk, and compliance teams to ensure ethical and regulated AI delivery.
- Own and contribute to architecture reviews, governance forums, and design approvals.
- Engage senior client stakeholders and shape proposals, bids, and AI solution strategies.
- Lead capability development across teams, mentoring senior and junior engineers.
- Strong background in software engineering or data engineering with applied AI (Python, SQL).
- Proven experience delivering AI/ML and generative AI systems in production.
- Deep understanding of LLMs, including: Prompt engineering, Embeddings, Fine-tuning, Retrieval-Augmented Generation (RAG).
- Demonstrated experience building and scaling agentic AI systems.
- Strong experience with AI system design, architecture, and distributed systems.
- Expertise in API-based backend development (e.g. FastAPI or similar).
- Experience with vector databases (e.g. Pinecone, Chroma).
- Experience with agent frameworks (e.g. LangChain, LangGraph, or similar).
- Strong understanding of evaluation frameworks for AI/agent systems.
- Experience implementing CI/CD pipelines and modern engineering practices.
- Exposure to MLOps / LLMOps principles.
- Experience working with at least one cloud hyperscaler (AWS, Azure, GCP, or Databricks).
- Strong Agile delivery experience (Agile, SAFe, XP, Jira, Confluence, etc.).
- Proven ability to lead technical programmes and cross-functional teams.
- Strong stakeholder management and client-facing leadership capability.
- Experience in Banking or Capital Markets (strong preference).
- Exposure to MCP (Model Context Protocol).
- Experience operating in regulated enterprise environments.
- Ability to contribute to ROI modelling, business cases, and AI value articulation.
- Experience contributing to bids, proposals, and go-to-market activity.
Artificial Intelligence Engineering Manager 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 team enjoys a hybrid working model, competitive salary, and comprehensive benefits, alongside ample opportunities for professional growth and development in the rapidly evolving field of AI and data within financial services. Join us to be at the forefront of transformative AI solutions, where your expertise will directly impact major banking institutions and drive meaningful change.
StudySmarter Expert Advice🤫
We think this is how you could land Artificial Intelligence Engineering Manager in London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in AI. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your AI projects or contributions to open-source initiatives. This gives potential employers a tangible sense of what you can bring to the table.
✨Ace the Interview
Prepare for those tricky interview questions by practising your responses. Focus on how you've led teams, tackled challenges, and delivered results in AI projects. Remember, confidence is key!
✨Apply Through Us
Don't forget to check out our website for job openings! Applying directly through us not only shows your interest but also helps you stand out in the crowd. We’re here to help you land that dream role!
We think you need these skills to ace Artificial Intelligence Engineering Manager in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of AI Engineering Manager. Highlight your experience with AI systems, architecture, and leadership in a way that resonates with our job description. 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 transformation in banking and how your background makes you the perfect fit. We love seeing genuine enthusiasm and a clear connection to our mission.
Showcase Your Technical Skills:Don’t hold back on showcasing your technical expertise! Mention specific technologies and methodologies you’ve worked with, especially those related to AI and machine learning. We’re keen to see your hands-on experience and how you’ve applied it in real-world scenarios.
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. Plus, it’s super easy to do!
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 around LLMs and generative AI. Be ready to discuss your experience with prompt engineering, embeddings, and how you've scaled agentic AI systems in the past. This role is all about technical credibility, so show them you know your stuff!
✨Showcase Your Leadership Skills
As a Senior Manager, you'll need to demonstrate your ability to lead multi-disciplinary teams. Prepare examples of how you've successfully managed projects, mentored engineers, and influenced stakeholders. Highlight your experience in delivering AI transformation strategies and how you've shaped proposals in previous roles.
✨Understand the Banking Landscape
Since this role focuses on banking transformation, it’s crucial to understand the financial services sector. Familiarise yourself with the challenges banks face regarding AI integration and compliance. Being able to speak to these issues will show that you’re not just technically savvy but also industry-aware.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during your interview. Be ready to explain your approach to designing API-based AI services and your experience with CI/CD pipelines. Practise articulating your thought process clearly, as this will help you stand out as a candidate who can bridge the gap between tech and business.
