Artificial Intelligence Engineer

McNally Recruitment Ltd; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

McNally Recruitment Ltd in London seeks a Lead AI Engineer for a Financial Services client. You will work in the office 1-2 days per week, partnering with business units to identify AI opportunities and drive end-to-end use cases from discovery to rollout.

You will design AI agents and AI-enabled workflows within a regulated banking environment, owning deployments and driving continuous improvement. The role requires delivering practical, scalable AI solutions while translating business needs

Qualifications

• Experience bridging business and technology in enterprise settings.
• Hands-on deployment of AI solutions in regulated environments.
• Strong understanding of business processes and stakeholder needs.
• Excellent written and spoken English.

Responsibilities

• Partner with business units to identify AI opportunities with measurable value.
• Lead AI use cases from discovery to rollout and ongoing improvement.
• Design and adapt AI agents and AI-enabled workflows.
• Own deployed AI agents with monitoring and optimisation.
• Facilitate workshops with business teams to shape high-impact use cases.
• Translate business requirements into technical solutions and explain concepts clearly.
• Capture learnings to develop reusable patterns and scalable approaches.

Skills

AI systems

LLM integration

Agentic workflows

Stakeholder management

Business-technology bridge

English communication

Education

Degree in CS/Engineering/DS

Tools

Cloud technologies

Data management

System integration

AI tools

Job description

We are working in collaboration to source a Lead AI Engineer for a Financial Services client in London, working in the office 1-2 days per week.

Your Responsibilities

• Partner closely with business units and support functions to understand workflows, pain points and opportunities where AI can create measurable value.
• Lead AI use cases end to end from discovery and scoping through prototyping, implementation, rollout and continuous improvement.
• Design, build and adapt AI agents and AI-enabled workflows to fit real business processes, enterprise constraints and the requirements of a regulated banking environment.
• Take ownership of deployed AI agents by monitoring their usage, performance and business impact and by driving ongoing optimisation in collaboration with stakeholders.
• Facilitate workshops and working sessions with business teams to identify, prioritise and shape high-impact AI use cases and practical implementation paths.
• Act as a bridge between business and technology by translating business requirements into technical solutions and explaining technical concepts in a clear and accessible way.
• Capture learnings from deployments and feed them back into reusable patterns, improvements and scalable approaches across the organisation.
• Degree in computer science, engineering, data science, business informatics, innovation management, finance, economics or a related field; equivalent practical experience is also welcome.
• Experience working effectively at the intersection of business and technology.
• Strong understanding of business processes and stakeholder needs with the ability to build trust and work closely with internal clients and cross-functional teams.
• Hands-on experience building and deploying practical technology solutions in complex enterprise environments.
• Strong understanding of modern AI systems and agentic workflows, including LLM integration, retrieval, tool use, context orchestration, evaluations, guardrails, observability and human-in-the-loop workflows.
• Ability to analyse complex workflows, simplify ambiguity and translate business requirements into practical and responsible solutions.
• Strong communication skills in English; German and additional languages relevant to client locations are an advantage.

Preferred Qualifications

• Experience in private banking, wealth management or financial services, ideally in areas such as client advisory, onboarding, KYC, investment processes, operations, risk or compliance.
• Familiarity with enterprise requirements related to security, governance, risk management, data privacy and regulatory expectations.
• Experience with modern software development, data management, system integration, cloud technologies, and relevant AI or automation tools.
• Experience supporting adoption, change and continuous improvement in complex organisational environments.