Finance Systems Integration Engineer
AnthropicSan Francisco, CA | Seattle, WAPosted 16 March 2026
Tech Stack
Job Description
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
We are seeking an experienced Finance Systems Integration Engineer to support our finance systems transformation at one of the fastest-growing AI companies. You'll design and build integrations connecting our ERP platform with critical financial applications and support our ERP implementation initiatives. As you master our integration landscape, you'll have opportunities to expand into Claude-powered AI automation and data pipeline development.
You'll build the integration backbone for one of the fastest-growing AI companies, with a front-row seat to how Claude transforms financial operations. This is a foundational role where you'll shape our integration architecture from the ground up, then expand into cutting-edge AI automation as our needs evolve. You'll work alongside teams building frontier AI systems while directly applying that technology to solve real financial operations challenges.
In this role you will:
Core Focus: Integration Development ERP Support
Design, build, and maintain integrations connecting ERP systems with downstream applications including ZipHQ, Brex, Navan, Clearwater, Payroll systems, Salesforce, and other critical financial platforms using Workato, MuleSoft, or similar iPaaS solutions
Support integration development and testing during the ERP implementation projects
Develop and maintain REST APIs, webhooks, and OAuth 2.0 authentication flows for secure system-to-system communication
Implement real-time and batch integration patterns supporting high-volume financial transactions
Establish monitoring, alerting, and error-handling frameworks to ensure integration reliability and data integrity
Document integration architectures, data flows, API specifications, and troubleshooting procedures
Collaborate with implementation consulting partners and vendors on technical integration requirements
Additional Scope: AI Automation Data Infrastructure
As you master our integration landscape, you'll have opportunities to expand into:
AI Agent Development
Build and deploy Claude-powered AI agents that automate financial operations including intelligent document processing, workflow automation, financial audit and reconciliations, and self-service reporting
Design agentic workflows that leverage Claude API capabilities integrated with ERP platform data and processes
Create automated validation and quality assurance processes for AI-generated outputs
Partner with Finance teams to identify automation opportunities and translate requirements into AI agent solutions
Data Pipeline Support
Support data pipeline development using Airflow for workflow orchestration and dbt for data transformation
Build and maintain data flows from ERP and other financial systems into BigQuery for analytics and reporting
Implement data quality checks and testing frameworks for financial data pipelines
Collaborate with Data Infrastructure team on pipeline architecture, performance optimization, and security monitoring
Support executive dashboards and financial analytics by ensuring timely, accurate data delivery
Governance Collaboration
Maintain comprehensive documentation for integrations, AI agents, and data pipelines
Support internal and external audits with technical evidence and system access reviews
Collaborate with Finance Systems Engineers on operational support, troubleshooting, and enhancement requests
Partner with Finance Operations, Accounting, FPA, Engineering, and Data Infrastructure teams to deliver holistic solutions
You may be a good fit if you:
Have 8+ years of experience in integration development, data engineering, or systems engineering rol ... (truncated, view full listing at source)
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