Senior AI Engineer (Financial Services):

Location: London with 4 days onsite

Contract: 12-month contract

Rate: £800 per day - Outside IR35

Our client is hiring a Senior AI Engineer to join a high-performing engineering team within a global alternative investment environment. This is a newly created role where you will help define the AI engineering approach and build production systems that support the identification, assessment, and progression of investment opportunities through internal workflows.

You will work closely with senior investment professionals to translate real business processes into reliable AI powered tools that are suitable for day-to-day use in a high-stakes environment. The focus is on production quality, reliability, traceability, and strong operational control rather than experimentation or prototypes.

What you will build:

• Production retrieval augmented generation systems across investment documents, third-party materials, and market data sources
• LLM based agent workflows with grounding, auditability, and tightly controlled response behaviour
• Hybrid search systems combining semantic and keyword-based retrieval across structured and unstructured data
• Document intelligence pipelines for complex materials including reports, tables, and regulatory content
• Multi step workflow orchestration using graph based execution and tool calling approaches
• Integrations with internal platforms and data systems using APIs and event driven design
• Full- stack internal tools including backend services, data pipelines, and user-facing applications for investment teams

Technology environment:

• Python, Java or .NET with SQL
• Azure preferred cloud environment
• Microservices architecture with Docker and CI CD pipelines
• Kafka and event driven systems
• Vector databases such as Pinecone or pgvector
• LLM orchestration frameworks such as LangChain or LangGraph
• Embeddings, retrieval systems, and evaluation methodologies
• Fine tuning approaches such as LoRA and QLoRA where applicable

Nice to have:

• Kubernetes in production environments
• Integration experience with enterprise platforms such as Salesforce or DealCloud
• Experience with regulated enterprise workflow systems

About you:

• 8 plus years of hands-on engineering experience with strong backend or full-stack capability
• Proven delivery of production AI or LLM based systems beyond proof-of-concept work
• Strong understanding of retrieval augmented generation and evaluation approaches
• Experience building systems in complex data rich environments
• Background in financial services or other regulated industries is valuable
• Exposure to investment workflows such as deal evaluation or investment decision processes is helpful
• Comfortable working directly with senior stakeholders and translating business needs into technical solutions

Domain exposure that would be beneficial:

• Capital markets, private equity, hedge funds, or investment banking environments
• Internal workflow systems supporting deal pipelines, approvals, or investment decision-making
• CRM and enterprise system integrations
• Strong governance, auditability, and controlled data access requirements