Lead the design and evolution of legal technology systems at Block, combining software engineering and legal domain expertise to build scalable AI-driven automation, integrations, and workflows across ELM, CLM, eDiscovery and data platforms.
Salary not listed
On-site7+ YOEFullstack Engineering
About the role
Responsibilities
Define and evolve the architecture of legal systems, ensuring they are scalable, cohesive, and adaptable over time.
Identify and drive high-impact opportunities to improve legal workflows through automation, integration, and AI.
Apply a strategic and creative approach to solving complex legal and operational challenges.
Lead the design and implementation of solutions leveraging AI (Claude, Harvey, internal LLM platforms).
Translate legal team experimentation into scalable, reliable, and production-ready solutions, establishing patterns, best practices, and guardrails that allow Legal to safely and effectively leverage AI.
Build and oversee integrations across DocuSign CLM, Brightflag, Tonkean, and AODocs and other Legal tools.
Develop APIs, automations, and data pipelines to connect systems and reduce manual effort.
Leverage Databricks/Snowflake and internal data platforms for analytics and AI workflows.
Provide technical leadership for eDiscovery and Information Governance workflows.
Operate as a hands-on technical lead, building and guiding long-term evolution.
Influence how Legal approaches technology with balance of innovation and risk.
Adapt to evolving priorities while maintaining long-term system design.
Requirements
7–10+ years in software engineering, systems engineering, or architecture roles.
Strong programming skills (Python, JavaScript, or similar).
Experience integrating SaaS platforms and APIs.
Hands-on AI tools experience (Claude, Codex, Copilot, etc.).
Ability to operate autonomously in ambiguous environments.
Deep ELM/eBilling experience (Brightflag preferred).
Strong eDiscovery experience (EDRM lifecycle).
Understanding of legal workflows (contracts, billing, discovery).
Experience with data platforms (e.g., Databricks, Snowflake).
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