Senior AI Engineering Leader for Enterprise GenAI

Senior AI Engineering Leader for Enterprise GenAI

Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
MBN Solutions

At a Glance

  • Tasks: Lead AI transformation projects and design scalable AI systems for major financial institutions.
  • Company: Join a leading professional services organisation at the forefront of AI innovation.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic role with leadership opportunities and collaboration across diverse teams.
  • Why this job: Make a real impact in the banking sector with cutting-edge AI technologies.
  • Qualifications: Strong background in software or data engineering with applied AI experience.

The predicted salary is between 80000 - 100000 £ 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
Required Skills & Experience
  • 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: Embeddings, 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)
  • 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

Senior AI Engineering Leader for Enterprise GenAI 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 the unique advantage of working at the forefront of AI transformation in the financial services sector, with ample opportunities for professional growth and development through mentorship and hands-on leadership experiences. We offer a hybrid work model that promotes work-life balance while empowering our employees to drive impactful change in major banking institutions.

MBN Solutions

Contact Details:

MBN Solutions Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior AI Engineering Leader for Enterprise GenAI

Tip Number 1

Network like a pro! Get out there and connect with folks in the AI and financial services space. Attend meetups, webinars, or industry events to meet potential employers and learn about opportunities that might not be advertised.

Tip Number 2

Show off your skills! Create a portfolio showcasing your AI projects, especially those involving generative AI and large-scale systems. This will give you an edge when chatting with hiring managers and help them see your hands-on experience.

Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and leadership skills. Be ready to discuss how you've led teams and delivered AI solutions in the past. Practice common interview questions related to AI engineering and stakeholder management.

Tip Number 4

Don’t forget to apply through our website! We’ve got loads of exciting roles, and applying directly can sometimes give you a better chance of landing that dream job. Plus, it shows you're genuinely interested in joining our team!

We think you need these skills to ace Senior AI Engineering Leader for Enterprise GenAI

AI Transformation Strategies
AI Engineering
Architecture Design
Generative AI Solutions
API-based Backend Development
Python
SQL

Some tips for your application 🫡

Tailor Your CV:Make sure your CV speaks directly to the role. Highlight your experience with AI systems, especially in financial services, and showcase any leadership roles you've had. We want to see how your skills align with our needs!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about AI and how your background makes you the perfect fit for this senior role. Don't forget to mention specific projects or achievements that relate to the job description.

Showcase Your Technical Skills:We’re looking for someone with a strong technical background. Be sure to include your experience with Python, SQL, and any relevant AI technologies. If you've worked with LLMs or generative AI, let us know how you’ve applied these in real-world scenarios!

Apply Through Our Website:We encourage you to apply through our website for a smoother 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!

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 hands-on experience with Python, SQL, and any relevant frameworks like FastAPI or LangChain. The more specific examples you can provide about your past projects, the better!

Understand the Business Side

Since this role is all about delivering measurable business value, be prepared to talk about how your AI solutions have positively impacted previous organisations. Think about ROI modelling and how you've articulated AI value in past roles—this will show that you can bridge the gap between tech and business.

Showcase Your Leadership Skills

This position requires strong leadership capabilities, so come ready to share examples of how you've led multi-disciplinary teams. Discuss your approach to mentoring engineers and managing stakeholder relationships, as well as any challenges you've faced and how you overcame them.

Prepare for Technical Questions

Expect some deep dives into technical topics during the interview. Brush up on your knowledge of API-based backend development, CI/CD practices, and MLOps principles. Being able to explain complex concepts clearly will demonstrate your expertise and communication skills.