AI Engineer - Agentic AI & LLM Solutions (Hybrid)

AI Engineer - Agentic AI & LLM Solutions

Location: London (Hybrid)
Contract: 12 months, Inside IR35

We are seeking an experienced AI Engineer to join a leading global investment house embarking on an ambitious AI transformation programme.

This is a high-impact contract role focused on building end-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 Responsilities:

AI Solution Design & Delivery

• Build end-to-end agentic AI and LLM-based solutions from concept to deployment
• Design AI architectures that map to real 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 with business stakeholders (traders, analysts, operations, research teams) to understand workflows and pain points
• Translate business requirements into AI 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 robust Python-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 of LLM capabilities and limitations - knows when AI is (and isn't) the right solution
• Experience designing AI solutions that map to real business problems, not just technical demos or proof-of-concepts
• Track record of delivering working AI solutions that create business value

Technical Skills

• Strong Python development skills - production-quality code, not just notebooks
• Ability to architect and build complete AI applications end-to-end
• Experience integrating AI capabilities into existing enterprise systems
• Understanding of software engineering best practices for AI systems
• Experience with specific LLM providers (OpenAI, Anthropic, Azure OpenAI)
• Familiarity with agent frameworks such as LangChain, LlamaIndex, AutoGen, or similar
• Experience building multi-agent systems and orchestration workflows
• Knowledge of prompt engineering and optimization techniques
• C#/.NET background for enterprise integration in financial services
• Experience with RAG pipelines and vector databases (Pinecone, Weaviate, ChromaDB, etc.)
• Understanding of embedding models and semantic search
• Knowledge of fine-tuning and model customization approache
• Experience working for Financial Services companies