Artificial Intelligence Engineer McCabe & Barton London Area, United Kingdom (Hybrid)
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AI Engineer - Agentic AI & LLM Solutions
Leading Investment House | London/Hybrid | Contract | Competitive Day Rate
About the Opportunity
We are seeking an experiencedAI Engineer to join a leading global investment house embarking on an ambitiousAI transformation programme.
This is a high-impact contract role focused on buildingend-to-end agentic AI and LLM-based solutions that solve real business problems across trading, operations, research, and front-office functions. You’ll work directly with business stakeholders to understand workflows, design intelligent automation solutions, and rapidly prototype working AI systems that deliver measurable value.
Key Responsibilities:
AI Solution Design & Delivery
*Buildend-to-end agentic AI and LLM-based solutions from concept to deployment
*Design AI architectures that map toreal business problems in investment banking
*Rapidly prototype and iterate AI solutions based on stakeholder feedback
*Move quickly from business brief to working solution - velocity is critical
*Own delivery independently with minimal supervision
Business Engagement & Requirements:
*Engage directly withbusiness stakeholders (traders, analysts, operations, research teams) to understand workflows and pain points
*Translate business requirements intoAI solution designs
*Demonstrate AI capabilities and educate stakeholders on art-of-the-possible
*Gather feedback and iterate solutions based on real user needs
*Communicate technical concepts to non-technical business audiences
Technical Implementation:
*Develop robustPython-based AI applications and agent systems
*Integrate LLM capabilities (OpenAI, Anthropic, Azure OpenAI) into business workflows
*Build agentic AI systems that can reason, plan, and execute multi-step tasks
*Implement RAG (Retrieval-Augmented Generation) pipelines for domain-specific knowledge
*Work with vector databases and enterprise data sources
*Integrate AI solutions with existing .NET/C# enterprise systems where required
Innovation & Best Practices
*Stay current with rapidly evolving LLM and agentic AI landscape
*Recommend appropriate AI frameworks and tools for different use cases
*Establish best practices for responsible AI deployment in regulated environment
*Balance innovation speed with security and compliance requirements
Essential Skills & Experience
AI & LLM Expertise
*Proven experience building end-to-end agentic AI or LLM-based solutions in production environments
*Deep understanding ofLLM capabilities and limitations - knows when AI is (and isn’t) the right solution
*Experience designingAI solutions that map to real business problems, not just technical demos or proof-of-concepts
*Track record ofdelivering working AI solutions that create business value
Technical Skills
*Strong Python development skills - production-quality code, not just notebooks
*Ability to architect and buildcomplete AI applications end-to-end
*Experience integrating AI capabilities into existing enterprise systems
*Understanding ofsoftware engineering best practices for AI systems
Desirable Skills & Experience
LLM & AI Frameworks
*Experience with specificLLM providers (OpenAI, Anthropic, Azure OpenAI)
*Familiarity withagent frameworks such as LangChain, LlamaIndex, AutoGen, or similar
*Experience buildingmulti-agent systems and orchestration workflows
*Knowledge ofprompt engineering and optimization techniques
Technical Depth
*C# / .NET background for enterprise integration in financial services
*Experience withRAG pipelines and vector databases (Pinecone, Weaviate, ChromaDB, etc.)
*Understanding ofembedding models and semantic search
*Knowledge offine-tuning and model customization approaches