Coinbase
Enterprise Engineer
Engineer who builds and runs integrations, workflows, and data pipelines for Coinbase's legal technology stack, centered on contract lifecycle and e-signature platforms.
Captured October 2026Still open as of Oct 11, 2026 ↗
The role
This role sits within the Enterprise Engineering Legal Platforms team, which maintains the legal toolchain that supports auditable, dependable, and scalable legal operations. The engineer owns core contract management architecture and adjacent legal platforms, working closely with Legal, Compliance, Security, and Engineering. The position is remote within the US, with periodic in-person team sessions.
What you would do
- Manage the architecture, workflows, and contract lifecycle setup for Ironclad, including links to systems upstream and downstream
- Construct and upkeep integrations through Workato and APIs to cut down manual intake and fulfillment effort
- Maintain and improve adjacent legal tools like Evisort, Brightflag, and DocuSign with attention to process flows and uptime
- Carry out data moves, historical loads, cross-system reconciliations, and continuous data cleanup
- Oversee access rights and credentials for legal systems, covering service accounts, token rotation, and access documentation
- Coordinate with Legal, Compliance, Security, and Engineering to deliver shared outcomes and push changes to production safely
What they asked for
- Three or more years running Ironclad, DocuSign, or comparable contract and e-signature tools in production, including intricate templates, workflows, and permission models
- Practical experience building integrations with Workato or similar iPaaS products, REST APIs, webhooks, auth flows, and structured payloads, including troubleshooting failures and mismatched data
- Track record of executing large-scale data migrations, bulk loads, and reconciliations while preserving integrity
- Ability to own a platform independently without detailed specs and explain technical matters clearly to non-technical stakeholders
- Responsible use of generative AI tools in daily work, with human review of outputs and measurable efficiency or quality gains
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