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Addepar is a global data and AI platform serving 1,400+ investment firms managing nearly $9 trillion in assets across 60 countries. The Reference Data team manages data reconciliation and curation for market data providers, building a single source of truth across public and alternative investment data products.
You will architect, lead, and drive execution of core AI capabilities powering Addepar's platform. This is a high-impact role for an engineer who thrives on applied AI and shipping at velocity. You will own end-to-end delivery of AI-native products, ensuring cutting-edge AI systems are hardened into robust, scalable, production systems.
Key responsibilities:
- Drive end-to-end execution of AI-native products from prototype to scalable production services
- Architect and productionize core AI platform components: LLMs and ecosystem (vector DBs, prompt tuning), agentic frameworks, agent capabilities (MCP, tool use, web browsing, computer use)
- Enforce technical discipline and operational excellence across AI products
- Rapidly iterate on AI products based on performance metrics and user feedback
- Lead evaluation and adoption of new AI technologies to keep Addepar at industry frontier
- Partner with product managers and engineering teams to translate strategic goals into technical realities
- Collaborate on platform architecture to meet growth and scalability needs
- Evaluate and drive strategic business and technology decisions
- Be a technical thought leader who educates and shares best practices
Required qualifications:
- B.S. or M.S. in Computer Science or equivalent technical field (or equivalent practical experience)
- Extensive software engineering experience
- Proven track record owning and shipping complex, production-grade systems
- Proven experience shipping and maintaining AI-native products or demonstrable passion through significant personal AI projects
- Deep ownership mindset and bias for action with passion for rapid shipping and iteration
Preferred:
- Specific experience with LLMs and agentic systems
- Hands-on experience with modern AI/LLM ecosystem (Databricks, Langchain, MLFlow)
- Advanced understanding of probabilistic systems underpinning modern LLMs
- Experience building AI products in accuracy-sensitive domains like finance
Note: Right to work in UK required from day one; visa sponsorship not available.
