Advanced Software Engineer

Summary

Relativity is a legal data intelligence company that develops AI-powered cloud technology for organizing data, discovering truth, and supporting high-stakes legal work. The Advanced Software Engineer will design, develop, and operate scalable distributed cloud services and AI infrastructure, while improving performance, reliability, cost efficiency, and model routing across the platform.

Responsibilities

• Contribute to the design, development, and operation of distributed, scalable, secure full-stack cloud services that process petabytes of data weekly
• Build performant, accessible user interfaces and extend backend services and data pipelines
• Consistently implement clean, testable, maintainable code to deliver customer impact
• Collaborate with a diverse group of teammates and product partners to solve problems, achieve team goals, and build AI-powered legal data solutions at massive scale
• Actively contribute to design and code reviews, providing constructive feedback to improve quality and maintainability
• Contribute to service ownership by supporting reliability efforts, including on-call rotations and incident response
• Improve throughput, latency, and cost per document across the platform: capacity headroom, token efficiency, and model routing and failover across regions
• Partner directly with the product teams building on the platform to shape its APIs and get new models and capabilities into production safely, including in government cloud environments

Skills

• 3+ years designing, building, and operating cloud‑native, distributed systems
• Hands‑on experience with APIs, event‑driven architecture, and data platforms
• Comfortable developing cloud-based, distributed services
• Ability to write clean, maintainable, well‑tested code using modern tooling and CI/CD
• Security‑ and reliability‑focused mindset with strong cross‑functional collaboration across engineering, product, and design
• Proficiency in Python and/or C#/.NET, with production experience running services on Kubernetes in a major cloud
• A track record of debugging and improving systems in production: distributed tracing, metrics, and comfort owning a service others depend on, on-call included
• Experience with full-stack development and modern UI frameworks
• Familiarity with performance or cost optimization
• Familiarity with AI-development tools like GitHub Copilot, Cursor or Claude Code
• Experience building on LLM APIs (Azure OpenAI, OpenAI, Anthropic): prompt and model versioning, evaluation, streaming, token accounting, or working within rate limits and provisioned throughput
• Experience with durable workflow engines (Temporal, Airflow, Step Functions) or high-volume batch and streaming data pipelines
• Interest in agentic systems — MCP, tool calling, and the infrastructure that makes them safe to run in a regulated environment

Qualifications

Must Haves

• 3+ years designing, building, and operating cloud‑native, distributed systems
• Hands‑on experience with APIs, event‑driven architecture, and data platforms
• Comfortable developing cloud-based, distributed services
• Ability to write clean, maintainable, well‑tested code using modern tooling and CI/CD
• Security‑ and reliability‑focused mindset with strong cross‑functional collaboration across engineering, product, and design
• Proficiency in Python and/or C#/.NET, with production experience running services on Kubernetes in a major cloud
• A track record of debugging and improving systems in production: distributed tracing, metrics, and comfort owning a service others depend on, on-call included

Nice to Haves

• Experience with full-stack development and modern UI frameworks
• Familiarity with performance or cost optimization
• Familiarity with AI-development tools like GitHub Copilot, Cursor or Claude Code
• Experience building on LLM APIs (Azure OpenAI, OpenAI, Anthropic): prompt and model versioning, evaluation, streaming, token accounting, or working within rate limits and provisioned throughput
• Experience with durable workflow engines (Temporal, Airflow, Step Functions) or high-volume batch and streaming data pipelines
• Interest in agentic systems — MCP, tool calling, and the infrastructure that makes them safe to run in a regulated environment

Benefits

• Health programs
• Retirement programs
• Wellness resources
• Discretionary time off (DTO)
• Parental leave for primary and secondary caregivers
• Two annual company breaks
• Home office stipend
• An equity program
• Volunteer opportunities
• Company-sponsored charitable programs
• An annual performance bonus
• Long-term incentives
• Hybrid/Remote work arrangement