2 days ago
Base Salary
$188k - $235k/yr
Responsibilities
- Drive end-to-end delivery of AI-native products from prototype through scalable production services.
- Architect, build, and productionize AI platform components involving LLMs, vector databases, prompt tuning, agentic frameworks, and agent capabilities such as 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 production systems.
Requirements
- 3–6+ years of professional backend software engineering experience.
- Experience with Python, Golang, gRPC, AWS, and Kubernetes.
- Proven ability to own and ship complex, production-grade systems.
- Experience shipping and maintaining AI-native products or features, or significant personal AI projects.
- Bachelor’s or master’s degree in computer science, statistics, mathematics, or another quantitative field, or equivalent experience.
- Preferred experience with LLMs, agentic systems, Databricks, LangChain, or MLflow.
- Preferred advanced understanding of the probabilistic systems underlying modern LLMs.
- Experience building AI products in accuracy-sensitive domains such as finance is preferred.
Benefits
- Base salary of $188,000–$235,000 USD, plus bonus, equity, and benefits.
- U.S. employment requires authorization to work for any employer without current or future visa sponsorship and authorization to begin on the first day.
- Addepar is an equal opportunity employer and provides reasonable accommodations for individuals with disabilities.
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.