The Role

We are currently seeking an AI Engineer to join our AI Platform team. The AI Platform 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.

As an AI Engineer, you will be responsible for designing, building, and productionizing the core AI capabilities that power our platform. This is a hands-on role where you will be on the frontier of applied AI with research and engineering, working directly with LLMs and agentic frameworks to translate cutting-edge concepts into robust, scalable products and capabilities. You will own the full lifecycle of AI-native products, from prototyping and evaluation to building the scalable backend systems that deliver them to our clients.

Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship (for example, employment-based visas such as H-1B, F-1/OPT, or similar), and must be authorized to begin work in the U.S. on their first day of employment.

What You’ll Do

• Design and build end-to-end AI-native products, from initial prototype all the way to scalable production services.
• Develop and productionize 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
• Rapidly iterate on AI products based on performance metrics and user feedback to drive continuous improvement.
• Drive the evaluation and adoption of new AI technologies and frameworks to keep Addepar on the frontier of the industry.
• Collaborate with product managers and other engineering teams to translate strategic goals into technical realities, abstracting AI complexity so they can iterate quickly.

Who You Are

• 1-3+ years of professional experience in backend software engineering, with expertise in programming languages/technologies like Python, Golang, gRPC, AWS, and Kubernetes.
• A strong, systems-level foundation in building and scaling backend services (e.g., understanding microservices, APIs, and concurrency).
• Proven experience shipping and maintaining AI-native products or features, or demonstrable passion through significant personal projects in AI.
• A strong bias for action, with a passion for shipping rapidly and iterating with feedback.
• Passion for proactivity, deep ownership, and a desire to learn and build on the frontier of AI.
• 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 technologies in the modern AI/LLM ecosystem, such as Databricks, Langchain, or MLFlow.
• (Preferred) Advanced understanding of the probabilistic systems underpinning modern LLMs.
• (Preferred) Experience building AI products in highly accuracy-sensitive domains such as finance is a plus.