Staff Software Engineer – Reference Data – AI/ML (UK)

Overview

In this role you will lead AI-enabled product development on Addepar’s Reference Data platform, turning data reconciliation and curation into scalable, production AI services. You’ll own end-to-end delivery of AI-native capabilities, working with LLMs, agentic systems, and platform components to empower wealth-management workflows. You’ll collaborate with product and engineering teams to translate strategies into robust, high-performance solutions and maintain shipping velocity. This is a high-impact, frontier-ai leadership position.

Responsibilities

• Own end-to-end delivery of AI-native products, from prototype to scalable production services
• Architect, build, and productionize AI platform components (LLMs, vector DBs, prompt tuning)
• Develop agentic frameworks and core agent capabilities (MCP, cross-platform tools, web browsing, computer use)
• Enforce technical discipline and operational excellence across AI products
• Iterate rapidly on AI products using performance data and user feedback
• Evaluate and adopt new AI technologies and frameworks to stay at the frontier
• Partner with product managers and engineering teams to convert goals into technical solutions
• Collaborate with engineering leads to define scalable platform architecture
• Provide technical leadership and prescriptive guidance across the team
• Assess strategic business and technology decisions for customers and the company

Key requirements

• B.S. or M.S. in Computer Science or equivalent practical experience
• Extensive software engineering experience
• Proven track record shipping complex, production-grade systems
• Experience shipping AI-native products or demonstrated passion via personal AI projects
• Deep ownership mindset and strong execution with high velocity
• Bias for action and ability to ship rapidly with feedback
• (Preferred) Experience with LLMs and agentic systems
• (Preferred) Hands-on experience with Databricks, Langchain, or MLFlow
• (Preferred) Understanding of probabilistic systems underlying modern LLMs
• (Preferred) Experience building AI products in finance is a plus

• ownership mindset
• strong collaboration
• bias for action
• LLMs and agentic frameworks
• vector databases
• prompt tuning

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