• Build and maintain backend services, APIs, and internal tooling used across product development teams • Improve infrastructure powering component distribution, asset management, documentation, and release workflows • Support and evolve the engineering monorepo, helping improve scalability, maintainability, and developer experience • Collaborate with frontend engineers and designers to ensure shared patterns and tooling are implemented consistently across products • Contribute to CI/CD pipelines, automation, testing, and deployment processes using tools like GitHub Actions • Help improve the reliability and performance of internal systems, including observability and monitoring workflows • Support engineers across product teams with adoption and integration of shared tooling and services • Contribute to documentation and developer tooling to improve discoverability and onboarding • Work on ongoing platform improvements, including: • Migration of legacy code and tooling • Documentation platform enhancements • Automation improvements • Sandbox and developer tooling improvements • Participate in architecture discussions and contribute practical, scalable engineering solutions

• Collaborate multi-functionally with product owners, designers, GTM teams, program managers and other Engineering team members to deliver for our clients • Conceive of, develop, and deliver novel solutions within a sophisticated and rich domain area. Learn and develop your career within a particularly challenging and growing part of the financial industry • Build both within the primary Navigator application and in other parts of Addepar's product ecosystem, bridging shared concerns for our clients across multiple product areas, with an investor-focused viewpoint

• Leverage the industry standard AI tools to architect, design, build, deploy and maintain Model Serving infrastructure that supports a world-class Detection Engine. • Own projects that scale our model serving and data processing services to handle 10x the traffic we serve today. • Own real-time, near real-time streaming pipelines, and online feature serving services. • Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing.

• Leverage the industry standard AI tools to architect, design, build, deploy and maintain Model Serving infrastructure that supports a world-class Detection Engine • Own projects that scale our model serving and data processing services to handle 10x the traffic we serve today • Own real-time, near real-time streaming pipelines, and online feature serving services • Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing