Artificial Intelligence Engineering Manager
MBN Solutions
Charing Cross, United Kingdom
3 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
£ 93KJob location
Charing Cross, United Kingdom
Tech stack
Agile Methodologies
Artificial Intelligence
Amazon Web Services (AWS)
Confluence
JIRA
Azure
Continuous Delivery
Continuous Integration
Information Engineering
DevOps
Distributed Systems
Python
Open Source Technology
Software Engineering
SQL Databases
Google Cloud Platform
Large Language Models
Multi-Agent Systems
Prompt Engineering
Generative AI
Backend
FastAPI
AI Platforms
Extreme Programming (XP)
Machine Learning Operations
Api Design
Databricks
Job description
- 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
Requirements
This is a senior leadership role combining hands-on technical credibility with programme leadership, stakeholder influence, and team development., * 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
Desirable Experience
- 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
About the company
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.