Software Engineer (Customer Facing Applied AI)

Join Addepar's Applied AI team as a Software Engineer, where you'll work closely with strategic clients to identify and build AI capabilities that transform their workflows. You'll prototype and iterate on solutions, design agent behavior, and partner with core engineering teams to ship products for all customers. This role offers the opportunity to shape the future of AI in finance and work in a dynamic, global environment.

• Identifying client needs and building AI-powered agents and tools from concept to production.
• Designing and implementing integrations with large language models (LLMs) and defining evaluation criteria for AI systems.
• Collaborating with core engineering teams to generalize client-specific work into product features and contributing to shared AI infrastructure.

• This role may require occasional work outside standard business hours to accommodate client time zones and up to 15% travel to client sites, including occasional overnight and multi-day engagements
• Experience working with LLM APIs (Claude, GPT, or similar) including function calling and structured outputs
• Professional experience with Python (the team's primary language)
• Experience with AI-assisted development tools (Claude Code, Codex, or similar)
• You've built something from zero to one. You're drawn to figuring out what to build, not just building what's specified
• BS/MS in Computer Science, Mathematics, or another quantitative field, or equivalent experience
• You see projects through from prototype to production and care about what the client experiences, not what the code does
• Prior professional software engineering experience
• A bias for action. You ship quickly, learn from feedback, and iterate
• Comfort with SQL for data exploration and building data-grounded AI workflows
• Experience building agentic systems (multi-step tool use, agent orchestration, durable workflows)
• Experience with additional backend languages (Java is valuable in our environment)
• Exposure to cloud infrastructure (AWS) and container-based deployments
• Familiarity with financial data (portfolios, transactions, securities, accounting)
• Experience with evaluation frameworks or methodologies for measuring AI system quality