Senior Software Engineer

Relativity•Illinois, IL

1d•$126,000 - $190,000•Hybrid

About The Position

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 are committed to expanding access to technology and supporting pro bono legal work. At Relativity, engineers don’t just write code. They shape how industries uncover critical insights, ensure compliance, and continuously evolve our platform using cloud-native architectures, AI capabilities, and modern developer tooling. Our AI powers privacy programs, identifies confidential information, and detects language indicating misconduct. We’re reimagining how legal professionals uncover truth at scale, and engineering is at the heart of that transformation. The Engineering Hub team is part of Engineering Systems at Relativity and focuses on building and operating internal infrastructure that enables engineers across the company to work more effectively. The team owns platforms such as the internal developer portal and software catalog, a developer metrics platform powered by a modern data stack, and an AI-assisted engineering knowledge base. This role is centered on improving developer experience through platform engineering, data, and AI—helping engineers discover tools, measure productivity, and safely adopt emerging AI capabilities.

Requirements

5+ years of professional software development experience
Strong proficiency in at least one backend language such as Python, Go, TypeScript, or C#
Experience designing and building cloud-native applications on Azure or AWS
Experience with data engineering concepts including pipelines, SQL, data modeling, and ETL/ELT workflows
Demonstrated ability to lead technical projects, including scoping, cross-team alignment, and proactive communication
Experience improving code quality, testing practices, and CI/CD automation, with the ability to manage technical debt strategically
Strong communication skills with the ability to convey complex technical concepts to non-technical stakeholders
Experience with observability tooling and using telemetry to drive system improvements
Automation
Data Analysis
Database Management
Network Architecture
Performance Optimizations
Problem Solving
Project Management
Software Development
System Designs
Technical Leadership

Nice To Haves

Hands-on experience with Backstage or similar internal developer portals
Familiarity with DORA metrics or engineering productivity frameworks
Experience with Databricks, dbt, or ADLS
Experience with Grafana or similar observability platforms
Experience building or integrating LLM-based systems, AI agents, or tool-calling protocols
Experience designing governance or discoverability frameworks for AI/ML tooling
Contributions to open-source projects within developer tooling, data engineering, or AI/ML ecosystems

Responsibilities

Design, build, and operate platform solutions that improve developer experience, including internal developer portal and software catalog capabilities
Build and maintain data pipelines supporting developer metrics and DORA reporting using tools such as ADLS, Databricks, dbt, and Grafana
Lead and contribute to architecture decisions for cloud-native, scalable platform systems
Decompose complex business problems into practical technical designs
Guide and mentor teammates through code reviews, pairing, and technical feedback
Partner with engineers across the organization to identify friction points and deliver impactful platform improvements
Own production systems by participating in on-call rotations, leading incident response, and driving root cause analysis
Contribute to roadmap planning by identifying opportunities to improve engineering effectiveness
Help define and build frameworks for AI tooling discoverability and governance, enabling responsible adoption of AI agents and tools