Artificial Intelligence Engineering Manager

MBN Solutions; Greater London; Hybrid; GBP 120,000 - 160,000; Full time

Job summary

MBN Solutions in London is seeking a Senior Manager – AI Engineer to lead AI transformation across Banking. This role combines hands-on technical credibility with program leadership to deliver enterprise AI systems.

You will drive strategy from architecture to production, manage cross-functional teams, and shape proposals and bids. The position requires deep experience in AI/ML, GenAI, and regulated banking environments, with hybrid working arrangements in London.

Qualifications

• Strong background in enterprise AI engineering and delivery leadership.
• Experience turning senior stakeholder visions into AI roadmaps.
• Proven track record delivering AI/ML systems in production.
• Experience leading cross-functional engineering teams.
• Experience in regulated enterprise environments (banking preferred).

Responsibilities

• Translate senior stakeholder vision into AI transformation strategies and roadmaps.
• Lead multi-disciplinary AI engineering teams and workstreams.
• Design and deliver enterprise-scale AI systems including GenAI.
• Collaborate with architects, data scientists, DevOps, and business stakeholders.
• Oversee CI/CD, MLOps, and LLMOps practices across teams.
• Engage with security, risk, and compliance for regulated AI delivery.
• Lead proposals, bids, and AI solution strategies.
• Mentor senior and junior engineers.

Skills

AI engineering leadership

Strategy & architecture

GenAI & LLMs

Distributed systems

API-based backend (FastAPI)

MLOps / LLMOps

Cross-functional leadership

Stakeholder management

Banking/Capital Markets experience

Python / SQL

Tools

FastAPI

LangChain

LangGraph

Pinecone

Chroma

AWS / Azure / GCP

CI/CD tooling

Job description

AI & Data | Financial Services | Technology & Transformation

London (Hybrid)

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