5 hours ago
London, United KingdomSenior
Responsibilities
- Drive end-to-end execution and delivery of AI-native products from prototype through scalable production services.
- Architect, build, and productionize core AI platform components involving LLMs, agentic frameworks, MCP, cross-platform tool use, web browsing, and computer use.
- Enforce technical discipline and operational excellence across AI products.
- Iterate on AI products using performance metrics and user feedback.
- Evaluate and adopt new AI technologies and frameworks.
- Partner with product managers and engineering teams to translate strategic goals into technical solutions.
Requirements
- Extensive professional experience in backend software engineering using technologies such as Python, Golang, gRPC, AWS, and Kubernetes.
- A proven record of owning and shipping complex, production-grade systems.
- Experience shipping and maintaining AI-native products or features, or significant personal AI projects.
- A strong ownership mindset, bias for action, and focus on rapid delivery and iteration.
- A BS or MS in Computer Science, Statistics, Mathematics, or another quantitative field, or equivalent experience.
- Preferred: experience with LLMs and agentic systems.
- Preferred: hands-on experience with Databricks, Langchain, or MLFlow.
- Preferred: advanced understanding of the probabilistic systems underlying modern LLMs.
- Preferred: experience building AI products in highly accuracy-sensitive domains such as finance.
Benefits
- The role is based in the United Kingdom and requires the applicant to have work authorization from the first day of employment.
- Addepar provides reasonable accommodation for individuals with disabilities.
- Addepar is an equal opportunity employer committed to inclusion and belonging.
Tech Stack
Categories
About Addepar
Addepar builds a SaaS platform for wealth and investment management firms to aggregate portfolio, market and client data, analyze holdings, and produce client reporting. The company sells software and data integrations used across investment operations, with APIs and a broad partner ecosystem to plug into other tools. Founded in 2009 and headquartered in New York, it is privately held and used by over a thousand firms globally to manage trillions in assets.