Sr. Software Engineer - Reference Data

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets.

Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo.

The Role We are currently seeking a Sr. Software Engineer with an AI background to join our Reference Data team.

The reference data team at Addepar is responsible to manage the data reconciliation and curation process for market data providers to build a single source of truth and provide alignment across public and alternative investment data products for the client to manage their investment portfolio.fAs an engineer on the team you will partner with product teams at Addepar to understand their business needs.

The team is focused on enabling and building disruptive, innovative solutions to transform the wealth technology landscape with AI across our product suite and is growing quickly.

You will be responsible for architecting, leading, and driving the execution of the core AI capabilities that power our platform. This is a high-impact role for an engineer who thrives on the frontier of applied AI and maintains a relentless focus on shipping. You will not just work with LLMs and agentic frameworks; you will own the end-to-end delivery of AI-native products, ensuring that cutting-edge AI systems are hardened into robust, scalable, and high-performance production systems.

Applicants must have, and maintain, the right to work in the United Kingdom from the first day of employment. Please note that visa sponsorship is not available for this role.

What You’ll DoDrive the end-to-end execution and delivery of AI-native products, moving from initial prototype to scalable production services with high velocity

Architect, build, and product ionize core components of our AI platform – including:

LLMs and the surrounding ecosystem (e.g., vector DBs, prompt tuning, etc.)Agentic frameworks

Core agent capabilities like MCP/ cross-platform tool use, web browsing, computer use Enforce technical discipline and operational excellence for all of our AI products

Rapidly iterate on AI products based on performance metrics and user feedback to drive continuous improvement

Lead the evaluation and adoption of new AI technologies and frameworks to keep Addepar on the frontier of the industry

Partner with product managers and other engineering teams to translate strategic goals into technical realities, abstracting AI complexity so they can iterate quickly

Collaborate closely with our engineering leads to define and implement our platform architecture to meet Addepar’s growth and scalability needs Evaluate and drive strategic business and technology decisions for the company and for customers

Be a technical thought leader in multiple areas who educates and shares best practices. Your contributions deliver strategic and prescriptive guidance

Who You AreB.S., or M.S. in Computer Science or similar technical field of study (or equivalent practical experience)
Extensive software engineering experience

Proven track record of owning and shipping complex, production-grade systems.

Proven experience shipping and maintaining AI-native products or features, or demonstrable passion through significant personal projects in AIDeep ownership mindset, seeing projects through to completion and raising the bar for execution across the teamA strong bias for action, with a passion for shipping rapidly and iterating with feedback BS/MS in Computer Science, Statistics, Mathematics, or another quantitative field, or equivalent experience[Preferred] Specific experience with LLMs and agentic systems[Preferred] Hands-on experience with…