Software Engineer - Workflow Platform

Addepar

About The Position

Addepar is investing in our Workflow Platform, which serves as the architectural backbone for building, orchestrating, and deploying critical financial workflows at a global scale. This platform integrates Addepar’s financial datasets, product suite, third-party vendors, and its native AI solution, Addison. The role involves evolving this platform into a self-service model to deliver workflows at scale to large customers, transforming manual financial processes into automated, agentic, tech-enabled workflows for sophisticated investors.

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 and use LLMs for tasks like navigating tech stacks, generating test cases, or optimizing performance.
Exceptional ability to translate technical constraints into clear business outcomes for stakeholders.
Work in close alignment with senior engineering to ensure technical recommendations are balanced with long-term business goals.
Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship.
Must be authorized to begin work in the U.S. on their first day of employment.

Nice To Haves

Familiarity with Temporal, n8n, Pipedream, or equivalent stateful orchestration systems.
Understanding of the challenges of long-running, distributed workflows at scale.

Responsibilities

Translate product vision into production-ready code, working with Product Managers to turn business goals into actionable plans and owning end-to-end execution.
Assist in scaling the platform by driving the transition to a self-service model and supporting geographic expansion, ensuring infrastructure performance.
Work at the intersection of workflow orchestration and Agentic AI to aid in executing complex, natural-language-driven tasks within a workflow context.
Take end-to-end ownership of service health, including participating in design docs, implementing monitoring/alerting, and ensuring distributed systems handle high-concurrency, long-running tasks.
Engage in technical reviews and pair programming to maintain high engineering standards, and help guide junior contributors to foster a culture of learning.