Software Engineer

Posting Type Hybrid/Remote Job Overview WHO WE ARE Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other high-stakes legal work where accuracy and trust are crucial. The world’s largest law firms, corporations, and government agencies rely on Relativity’s legal AI software to securely surface and manage the most relevant and impactful information in their matters. Beyond our commercial impact, we’re deeply committed to expanding access to technology for academic institutions through Relativity Academic and supporting pro bono legal work through Justice for Change. WHAT WE DO At Relativity, engineers don’t just write code. They build the systems that power AI-driven workflows at massive scale, enabling customers to uncover insights and act on complex data with confidence. aiR Services Team The aiR Services team builds the shared backend platform that powers Relativity’s generative AI products. These systems enable secure and scalable access to foundation models across the aiR Suite while handling challenges such as limited model capacity, global data privacy requirements, and fair usage across products and customers. The team works on high-throughput, distributed systems that route AI traffic across regions and providers, protect downstream services from reliability risks, and optimize cost and performance at scale. If you’re excited about building platforms that power an entire product suite, working with generative AI systems in production, and solving distributed systems challenges at global scale, this is a high-impact team to join. Job Description and Requirements ABOUT THE ROLE As a Software Engineer, you will build and operate backend services that power Relativity’s generative AI platform, aiR. You will work at the intersection of distributed systems, cloud infrastructure, and applied AI, helping to deliver reliable, scalable systems that sit on the critical path of AI-powered workflows. This role reports to the Manager of Software Engineering and provides the opportunity to work on multi-region, multi-cloud systems that handle large-scale AI traffic and complex orchestration challenges. WHAT YOU’LL DO Design and build performant, scalable, and secure backend services with a strong focus on quality, not just meeting requirements Collaborate with a software development team to deliver high-quality, reliable systems that operate at massive scale Develop and maintain systems that support high-throughput AI workloads, including asynchronous job orchestration and distributed processing Write comprehensive unit and integration tests supported by static analysis and thoughtful test strategy development Contribute to improving engineering processes by recommending enhancements to tools, workflows, and practices Participate in pair programming to improve software quality and share design and implementation knowledge Contribute to building systems that route and manage AI traffic efficiently while maintaining reliability and fairness across workloads WHAT WE’RE LOOKING FOR Required Bachelor’s degree in Computer Science or a related field, or equivalent practical experience Experience building backend services using languages such as C#, Python, or similar Understanding of software engineering disciplines and the ability to work across multiple layers of the application stack Strong foundational knowledge of distributed systems, scalability, and backend service design Preferred Understanding of DevOps principles and experience with tools such as GitHub Actions Experience working with large language model (LLM) APIs or generative AI systems Experience designing and building scalable systems in Azure or other cloud platforms Experience with Kubernetes, serverless technologies, and cloud-native architectures Familiarity with domain-driven design and event-driven architecture Experience with AI-driven development practices or AI-assisted coding tools Awareness of emerging technology trends and their practical application in engineering WHY WE COULD BE A GREAT FIT Impactful AI Platform Build foundational systems that power Relativity’s generative AI capabilities and enable products across the aiR Suite. Distributed Systems at Scale Work on high-throughput, multi-region services that handle large volumes of AI traffic reliably and efficiently. Cutting-Edge Technology Gain hands-on experience with generative AI systems, cloud-native infrastructure, and modern distributed architectures. Growth Opportunity Develop deep expertise in backend systems, cloud platforms, and AI-driven services while working on highly visible, impactful projects. Collaborative Culture Work with a team that values strong engineering fundamentals, shared ownership, and continuous learning. Compensation and Benefits Competitive salary, health and retirement programs, wellness resources, discretionary time off (DTO), parental leave for primary and secondary caregivers, company-wide breaks, home office stipend, and an equity program. Relativity is committed to competitive, fair, and equitable compensation practices. This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives. The expected salary range for this role is between following values: $79,000 and $119,000 The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position. Required Skills: Automation, Documentations, Engineering Design, Problem Solving, Process Improvements, Project Management, Quality Assurance (QA), Research and Development, System Integration, Troubleshooting