AI Engineer

Artificial Intelligence Engineer McCabe & Barton London Area, United Kingdom (Hybrid) Save Apply 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