At a Glance
- Tasks: Design and deploy AI systems for banking transformation, from prototyping to production.
- Company: Leading professional services firm focused on AI in financial services.
- Benefits: Competitive salary, hybrid work, and opportunities for professional growth.
- Other info: Dynamic role with leadership opportunities and mentorship for junior engineers.
- Why this job: Join a high-performing team and shape the future of banking with AI.
- Qualifications: Strong software engineering skills and experience in AI/ML systems.
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 Slough employer: MBN Solutions
As a leading professional services organisation, we offer an exceptional work environment for AI Engineering Consultants in London, where innovation meets collaboration. Our hybrid work model promotes a healthy work-life balance, while our commitment to employee growth through mentorship and leadership opportunities ensures that you can advance your career in the rapidly evolving field of AI within banking transformation. Join us to be part of a high-performing team dedicated to delivering cutting-edge AI solutions that make a real impact in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Artificial Intelligence Engineering Consultant in Slough
✨Tip Number 1
Network like a pro! Get out there and connect with people 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, prototypes, and any relevant work you've done. This will give you an edge during interviews and help demonstrate your hands-on experience.
✨Tip Number 3
Prepare for those interviews! Research common interview questions for AI engineering roles and practice your responses. Be ready to discuss your experience with Python, machine learning, and how you've tackled challenges in past projects.
✨Tip Number 4
Don't forget to apply through our website! We have loads of exciting opportunities waiting for you. Tailor your application to highlight your experience in AI and banking transformation, and let us help you land that dream job!
We think you need these skills to ace Artificial Intelligence Engineering Consultant in Slough
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly 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 align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about AI in banking and how your background makes you a perfect fit. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects:If you've worked on any AI or machine learning projects, make sure to include them! Whether it's a prototype or a full-scale deployment, we want to know what you've built and how it relates to the role. Visuals or links to your work can really help!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you'll find all the details you need about the role and our company culture there!
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 machine learning. Be ready to discuss your experience with Python, SQL, and any relevant frameworks like LangChain or LangGraph. The more you can demonstrate your technical expertise, the better!
✨Understand the Banking Landscape
Since this role is focused on banking transformation, it’s crucial to understand the specific challenges and opportunities within the financial services sector. Familiarise yourself with current trends in banking technology and be prepared to discuss how AI can address these issues.
✨Showcase Your Problem-Solving Skills
Be ready to share examples of how you've tackled complex problems in previous roles. Think about times when you designed, built, or deployed AI systems, and how you collaborated with teams to deliver solutions. Highlighting your hands-on experience will set you apart.
✨Engage with Stakeholders
This role involves a lot of client interaction, so practice how you would communicate technical concepts to non-technical stakeholders. Prepare to discuss how you’ve successfully engaged with clients in the past and how you can bridge the gap between technical and business teams.
