Backend Engineer, AI Platform & Distributed Systems — Remote

Relativity; Phoenix (AZ); Hybrid; USD 79,000 - 119,000; Full time

Benefits offered by this job

Health benefits

Retirement plan

Wellness resources

DTO (Discretionary Time Off)

Parental leave

Company breaks

Home office stipend

Equity program

Job summary

Relativity, a leader in legal data intelligence, seeks a Software Engineer to build backend services powering aiR, Relativity's generative AI platform. You will work on distributed systems across multi-region, multi-cloud environments to deliver reliable, scalable AI workflows.

Join a team that values engineering fundamentals, collaboration, and continuous learning. The role offers hybrid work options in Phoenix with competitive compensation and benefits.

Qualifications

• Bachelor’s degree in CS or related field or equivalent experience.
• Backend services with languages such as C# or Python.
• Understanding of distributed systems and scalability.

Responsibilities

• Design and build scalable backend services for aiR platform.
• Collaborate with a software development team to deliver reliable systems at scale.
• Develop systems supporting high-throughput AI workloads.
• Write unit and integration tests with static analysis.
• Contribute to improving engineering processes and tools.
• Participate in pair programming to improve software quality.
• Build systems that route and manage AI traffic with reliability and fairness.

Skills

Backend services

Distributed systems

Cloud platforms

Python

C#

Testing (unit/integration)

DevOps basics

Education

Bachelor’s degree in Computer Science or related

Tools

GitHub Actions

Kubernetes

Azure

Job description

Relativity, a leader in legal data intelligence, seeks a Software Engineer to build backend services powering aiR, Relativity's generative AI platform. You will work on distributed systems across multi-region, multi-cloud environments to deliver reliable, scalable AI workflows.

Join a team that values engineering fundamentals, collaboration, and continuous learning. The role offers hybrid work options in Phoenix with competitive compensation and benefits.