Asks for

The ad says“Proficiency in Python and/or C#/.NET, with production experience running services on Kubernetes in a major cloud.”
The ad says“Hands‑on experience with APIs, event‑driven architecture, and data platforms”
The ad says“Proficiency in Python and/or C#/.NET, with production experience running services on Kubernetes in a major cloud.”
The ad says“Ability to write clean, maintainable, well‑tested code using modern tooling and CI/CD”
The ad says“Hands‑on experience with APIs, event‑driven architecture, and data platforms”
The ad says“3+ years designing, building, and operating cloud‑native, distributed systems”
The ad says“A track record of debugging and improving systems in production: distributed tracing, metrics, and comfort owning a service others depend on, on-call included.”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”
The ad says“Hands‑on experience with APIs, event‑driven architecture, and data platforms”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”
The ad says“Proficiency in Python and/or C#/.NET, with production experience running services on Kubernetes in a major cloud.”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”
The ad says“Proficiency in Python and/or C#/.NET, with production experience running services on Kubernetes in a major cloud.”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”
The ad says“Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting”

Values

The ad says“Interest in agentic systems — MCP, tool calling, and the infrastructure that makes them safe to run in a regulated environment.”
The ad says“Experience with durable workflow engines (Temporal, Airflow, Step Functions) or high-volume batch and streaming data pipelines.”
The ad says“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.”
The ad says“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.”
The ad says“Experience with durable workflow engines (Temporal, Airflow, Step Functions) or high-volume batch and streaming data pipelines.”
The ad says“Familiarity with AI-development tools like GitHub Copilot, Cursor or Claude Code.”
The ad says“Familiarity with performance or cost optimization.”
The ad says“Familiarity with AI-development tools like GitHub Copilot, Cursor or Claude Code.”
The ad says“Experience with full-stack development and modern UI frameworks.”
The ad says“Familiarity with AI-development tools like GitHub Copilot, Cursor or Claude Code.”
The ad says“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.”
The ad says“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.”
The ad says“Familiarity with performance or cost optimization.”
The ad says“Experience with durable workflow engines (Temporal, Airflow, Step Functions) or high-volume batch and streaming data pipelines.”
The ad says“Experience with durable workflow engines (Temporal, Airflow, Step Functions) or high-volume batch and streaming data pipelines.”
The ad says“Experience with full-stack development and modern UI frameworks.”

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 harness AI tools to architect, optimize, and deliver scalable software faster and shape the future of legal technology. They shape how industries uncover critical insights, ensure compliance, advance access to justice and continuously evolve our platform using the latest technologies, including 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.

Our team builds the AI platform that Relativity's aiR products run on. We own the systems that orchestrate large-scale document review by LLM — durable workflows that carry a job through millions of documents — and the gateway that routes every model request across cloud regions and sovereign environments while managing capacity, throughput, and cost. Every AI feature our customers touch runs through our stack, and the work is equal parts distributed systems, LLM infrastructure, and reliability engineering.

If you’re passionate about solving hard problems, designing for scale, and building tools that matter—while working in a culture that values transparency, innovation, and shared success— Relativity offers the opportunity to make a measurable difference in the marketplace.

Job Description and Requirements

What You’ll Do

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.

What We’re Looking For

Required

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.

Preferred

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.

Why We Could Be A Great Fit

Impactful Mission: Organize Data, Discover the Truth and Act on It - Our customers include Fortune 500 enterprises and leading law firms managing high-stakes matters on our platform.

Growth Path: Engineers gain exposure across the stack, from distributed systems to AI-enabled workflows, accelerating career growth.

Engineering Culture: Continuous delivery, strong observability, and end-to-end ownership.

Inclusive Environment: Diverse backgrounds and perspectives make us stronger.

Community Impact: Volunteer opportunities and company-sponsored charitable programs.

Compensation & Benefits: Competitive salary, health and retirement programs, wellness resources, discretionary time off (DTO), parental leave for primary and secondary caregivers, two annual company 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:

$103,000 and $155,000

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:

Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, Troubleshooting