Senior Director, Software Engineering - Contract Intelligence

Role overview Set engineering direction and lead delivery for a portfolio of contract intelligence products and the shared platform capabilities that support them. The senior leader will align teams around an integrated technical roadmap, building secure, scalable services and AI features that multiple products can use while preserving the needs of each experience.

Responsibilities - Lead engineering strategy, organization, and execution across contract intelligence products and their shared platform components. - Guide architecture for common data models, database services, identity and access management, AI assistants and agents, and interfaces spanning APIs, user interfaces, and MCP servers. - Turn product priorities into an executable roadmap with dependable delivery, clear ownership boundaries, and sound technical tradeoffs. - Partner with product, design, applied AI, core platform, and cloud operations teams to deliver customer value. - Track delivery predictability, reliability objectives, defects, performance, and operational health; address risks to quality and maintainability. - Set responsible AI practices for customer-facing features, including accuracy, privacy, security, permissions, transparency, and human oversight. - Develop managers and technical leaders, strengthen succession, and build an environment where distributed teams can do strong work.

Requirements - Degree in computer science or engineering, or equivalent practical experience. - At least 10 years in software engineering, including five or more years leading multi-team organizations with managers and senior technical leaders. - Ownership of engineering outcomes for a substantial product portfolio, platform, or technical domain, tied to customer adoption and business value. - Deep experience with cloud SaaS, distributed services, APIs, enterprise integrations, and user-facing applications. - Track record building shared components used across products, such as data models, database services, and identity systems. - Hands-on technical fluency in production AI and large language model features, agents, and assistants, including quality, privacy, reliability, and cost considerations. - Strong partnership with product and design, executive communication, and ability to translate customer priorities into measurable delivery.

Nice to have - Experience leading AI-enabled products, agent architectures, or orchestration interfaces such as MCP. - Knowledge graph or other data-rich enterprise platform experience. - Background in contract lifecycle management, legal technology, workflow automation, or enterprise SaaS. - Experience scaling engineering organizations and operating practices in compliance-driven environments.