Senior Manager – AI Engineer (Capital Markets)
AI Scaling & Transformation | AI & Data | Financial Services
London (Hybrid)
Salary: £80,000 – £93,000
Date Published: 21 Apr 2026
About the Role
A leading professional services organisation is seeking a Senior Manager – AI Engineer to join its AI & Data Financial Services practice, focused on transforming the financial services industry through advanced AI engineering, data platforms, and scalable machine learning systems.
This role sits at the forefront of AI-driven transformation in Capital Markets, helping major financial institutions design, build, and operationalise enterprise-grade AI solutions. You will work across strategy, architecture, implementation, and optimisation of AI systems that drive measurable business impact.
The team works across banking, insurance, capital markets, and investment & wealth management, enabling organisations to modernise core operations, enhance customer experience, improve risk management, and drive automation at scale.
Key Responsibilities
1. Translate senior client vision into AI delivery roadmaps and implementation plans aligned to digital transformation goals
2. Collaborate with Enterprise, Data, Application, DevOps, and AI/ML architects to design and deploy scalable AI solutions
3. Evaluate and select appropriate technologies across open-source and commercial AI ecosystems
4. Lead the delivery of AI-powered applications using Agile methodologies
5. Work with security and risk teams to ensure ethical, compliant, and secure AI systems
6. Support technical governance, design reviews, and architecture approvals
7. Engage with senior stakeholders and contribute to proposals, bids, and solution shaping
8. Mentor and develop junior engineers within inclusive, high-performing teams
Required Skills & Experience
9. Strong background in software or data engineering with applied AI (Python, SQL)
10. Experience in Financial Services, ideally Capital Markets
11. Hands-on experience designing agentic AI systems and LLM-based architectures
12. Knowledge of prompt engineering, embeddings, fine-tuning, and RAG patterns
13. Experience with vector databases (e.g., Pinecone) and agent frameworks (e.g., LangChain, LangGraph, or similar)
14. Experience building API-based services (e.g., FastAPI)
15. Strong understanding of modern data architectures and MLOps / LLMOps practices
16. Experience with CI/CD pipelines for ML or AI systems
17. Familiarity with at least one cloud hyperscaler (AWS, Azure, GCP, Databricks)
18. Strong stakeholder management and leadership skills across technical and business teams
19. Experience contributing to go-to-market activity, bids, and solution proposals
Additional Information
20. Hybrid working model (London-based with flexible remote options)
21. Opportunity to lead large-scale AI transformation programmes in global financial institutions
22. Focus on innovation, responsible AI, and enterprise-scale deployment
23. Strong emphasis on career development, leadership growth, and technical mastery
If you want, I can also:
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25. make it sound more “recruiter salesy”
26. or tailor it for passive candidates (higher response rate version)