Top Legal Tech Software Engineer Jobs in Washington DC,

The Director of Engineering provides strategic leadership, oversees AI-enabled systems development, fosters team culture, and collaborates with stakeholders to align technical roadmaps with business goals.

The Senior ServiceNow Developer designs and builds solutions on the ServiceNow platform, working with stakeholders to enhance legal practice operations and improve service delivery through automation and integrations.

Provide development and support for the firm's financial applications: design, develop, test, and implement custom solutions; maintain databases and SQL; build integrations and automations using APIs and AI services; support Windows desktop/application issues; collaborate with business owners; document changes; recommend process improvements while safeguarding confidential financial data.

The Senior Full Stack Developer will build end-to-end solutions, collaborate in a remote environment, and write technical documentation. The role requires expertise in Ruby on Rails and various programming paradigms.

Design and implement custom SharePoint solutions, including web parts and integrations, while optimizing platform performance and collaborating with stakeholders.

The Senior Software Development Engineer will develop applications using modern programming languages, provide leadership and mentoring, ensure software quality, and lead software improvement initiatives.

Perform technical code review and analysis to determine originality and function, prepare memos and expert reports, rebut other experts, communicate with counsel and clients, prepare testifying experts, manage multiple engagements, and supervise junior staff.

Join Litify as a Junior Salesforce Developer to build high-quality Salesforce applications within two-week sprints. Write tested Apex and client-side code (LWC/Aura/JS), collaborate on product and process improvements, leverage AI coding tools to accelerate delivery, and apply the Salesforce platform to legal-industry workflows.

Own product problems end-to-end: gather requirements, build full‑stack features using AI, verify production quality, monitor and support services, and iterate to improve outcomes.

Lead the Data & Cloud Platform for the AI organization, building cloud runtime, unified data access layers, agent memory/context systems, and data ingestion/transformation pipelines. Split time between hands-on engineering and managing a small team, set platform patterns, ensure privacy-aware data handling, and partner with product and governance teams to scale maintainable, cost-effective infrastructure for AI workloads.