Staff Software Engineer (Ruby on Rails)

About this role

Here’s a summary of the role: As a Staff Ruby on Rails Engineer at Diligent, you will set technical direction for secure, scalable, and high-performing SaaS applications and services that power our governance platform. This role is ideal for you if you thrive on solving the hardest technical problems, shaping architecture across multiple teams, and driving how the organization builds software — including how we responsibly adopt AI into our engineering practices and products.

You will own critical systems end-to-end, partner closely with Product, Security, DevOps, and other engineering leaders to shape technical roadmaps, and mentor engineers across the department. A key part of this role is helping define our AI strategy: embedding AI responsibly into our systems and workflows, advising on where AI tools and capabilities can meaningfully improve delivery, and raising the bar on how the team uses them safely and effectively.

Here’s a breakdown of what you’ll do (not all of it, just the important stuff): Champion the design, delivery, and evolution of secure, scalable Ruby on Rails applications and services, driving architecture decisions across multiple teams and codebases, with responsibility for scalability, reliability, and the underlying infrastructure required to run them effectively. Set technical direction for major projects and platform initiatives, from solution design and prototyping through implementation and production ownership.

Own and evolve the technical roadmap by identifying, shaping, and driving new technical initiatives and investments. Develop and evolve web applications and services with a strong focus on scalability, maintainability, reliability, and long-term platform health. Identify systemic pain points across services and propose pragmatic architectural improvements, including decomposition of monoliths and evolution toward service-oriented or microservices patterns where it adds value.

Partner effectively with Product, QA, Security, and other engineering leaders to shape technical roadmaps, ensure compliance, and deliver working software into production. Help teams move forward by resolving technical ambiguity, identifying cross-team dependencies, and providing clear technical direction where needed. Pioneer and enable the responsible use of AI in engineering workflows — advising on where AI-assisted coding, debugging, prototyping, and other AI capabilities improve speed or quality, and helping teams adopt them with appropriate human validation, monitoring, and governance.