Software Engineer - Workflow Platform

Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. The role focuses on developing the Workflow Platform, transforming financial processes into automated workflows and ensuring the platform scales effectively for global operations.

Responsibilities:

• Translate product vision into production-ready code. You’ll work closely with global Product Managers to turn broad business goals into actionable plans, owning the end-to-end execution and navigating technical roadblocks to ensure consistent, high-quality delivery
• Help drive the transition to a self-service model and assist with geographic expansion, ensuring our infrastructure remains performant across new global regions, as our team and technology scales
• Work at the intersection of workflow orchestration and Agentic AI, helping to aid in the execution of complex, natural-language-driven tasks within a workflow-oriented context
• Take end-to-end ownership of service health. This includes participating in design docs, implementing robust monitoring/alerting, and ensuring our distributed systems can handle high-concurrency, long-running, fault tolerant tasks without issue
• Engage in deep technical reviews and pair programming sessions to maintain high engineering standards. While you will receive direct mentorship from Staff Engineers to sharpen your architectural skills, you will also help guide more junior contributors as the team scales, fostering a culture of continuous learning and rigorous development

Requirements:

• Highly proficient in Python and Java
• Practical experience (2-5 years) building robust, service-oriented architectures (ideally on AWS)
• Thorough understanding of web application design patterns, modern deployment methodologies, and scalability
• Embrace AI-first development practices
• Exceptional at translating technical constraints into clear business outcomes for stakeholders across different domains
• Familiarity with Temporal, n8n, Pipedream, or equivalent stateful orchestration systems