Manager – AI Engineer (Banking & Data Transformation)
AI & Data | Financial Services | Technology & Transformation
London (Hybrid)
Salary: £60,000 – £75,000
Overview
A leading professional services organisation is seeking a Manager – AI Engineer to join its AI & Data Financial Services team, focused on delivering AI-driven transformation across the banking sector.
This role sits within a high-performing engineering and delivery team helping financial institutions design, build, and scale AI systems and data platforms. You will lead small technical squads working across AI prototyping, architecture design, and production deployment of machine learning and generative AI solutions.
The role combines hands-on technical delivery with leadership responsibilities across AI engineering, architecture decision-making, and stakeholder engagement.
Key Responsibilities
1. Translate client vision into AI architecture strategies and delivery roadmaps
2. Lead technical squads delivering AI prototypes, experiments, and production systems
3. Collaborate with engineers, data scientists, architects, and business stakeholders
4. Own technical decision-making across: build vs buy decisions deployment and serving patterns integration and system design
5. Work with security and risk teams to ensure ethical and compliant AI systems
6. Support technical governance including design reviews and architecture approvals
7. Build strong relationships with client stakeholders
8. Contribute to business cases, proposals, and ROI estimation for AI solutions
9. Mentor and develop junior team members and contribute to internal capability building
Required Skills & Experience
10. Strong background in software or data engineering with applied AI (Python, SQL)
11. Experience building API-based systems (e.g. FastAPI preferred)
12. Strong understanding of LLMs: prompt engineering, embeddings, fine-tuning, RAG
13. Experience delivering agentic AI solutions and managing delivery scope
14. Knowledge of evaluation frameworks for AI/agent systems
15. Experience with CI/CD tooling and modern engineering practices
16. Exposure to MLOps / LLMOps principles (desirable)
17. Experience in Financial Services, ideally Banking
18. Experience with: vector databases (e.g. Pinecone) agent frameworks (e.g. LangChain, LangGraph, or similar) MCP (preferred)
19. Strong understanding of modern data architectures and system design
20. Experience working with at least one cloud hyperscaler (AWS, Azure, GCP, Databricks)
21. Strong stakeholder management and communication skills
22. Ability to work independently and lead delivery in complex environments
23. Experience writing technical documentation and AI business cases
Additional Information
24. Hybrid working model (London-based)
25. Focus on enterprise AI transformation in banking and financial services
26. Mix of hands-on engineering + technical leadership
27. Exposure to cutting-edge agentic AI systems and production deployments
28. Strong emphasis on career development, leadership, and technical growth