IT & Software

Sr. Software Engineer - Reference Data

Addepar

Edinburgh · City of Edinburgh · United Kingdom

Overview

As Sr. Software Engineer on Addepar’s Reference Data team, you will architect and deliver AI-native capabilities that power our platform. You’ll own end-to-end AI product delivery, from prototypes to scalable production services, focusing on reliability and performance. You’ll work with product teams to translate goals into robust AI solutions, shaping the wealth-technology landscape. This role combines hands-on execution with thought leadership in AI across the platform.

Responsibilities
  • Drive end-to-end AI product delivery from prototype to production services
  • Architect and productionize core AI platform components (LLMs, vector databases, prompt tuning)
  • Develop agentic capabilities including MCP and cross-platform tool use, web browsing, and computer interactions
  • Enforce technical discipline and operational excellence across AI products
  • Iterate AI products using performance metrics and user feedback for continuous improvement
  • Evaluate and adopt new AI technologies to stay at the frontier
  • Collaborate with product managers and other engineering teams to translate strategic goals into technical solutions
  • Define and implement platform architecture with growth and scalability in mind
  • Provide technical leadership and prescriptive guidance on AI best practices
Key requirements
  • B.S. or M.S. in Computer Science or similar field (or equivalent practical experience)
  • Extensive software engineering experience
  • Proven track record shipping complex, production-grade systems
  • Experience shipping/maintaining AI-native products or demonstrable AI-related projects
  • Strong ownership mindset and bias for action
  • Experience with LLMs and agentic systems (preferred)
  • Hands-on experience with modern AI/LLM tools (Databricks, Langchain, MLFlow - preferred)
  • Understanding of probabilistic systems underpinning LLMs (preferred)
  • Experience building AI products in finance or highly accuracy-sensitive domains (a plus)
  • ownership mindset
  • bias for action
  • collaboration
  • LLMs and agentic frameworks
  • vector databases and prompt tuning
  • MCP/cross-platform tool use

Reference: WJ-747_30164765

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