Posting Type
Remote/Hybrid
Job Overview
We’re looking for an engineer who designs, builds, and operates large-scale distributed systems under strict availability SLOs. Enrichment turns more than a petabyte a month of raw, unstructured data (files, mailboxes, drives, cloud containers) into structured legal intelligence, with jobs ranging from a few files to a billion. These systems require 99.99% uptime and sub-10-second job response, and when they’re down or wrong, customers feel it immediately.
You’ll drive the shift from batch pipelines to streaming-first processing on Kubernetes, Spark, and Temporal, set technical standards, and raise the bar for the engineers around you. This is a hands-on individual-contributor role.
You’ll also mentor senior and staff engineers, set standards other teams adopt, influence across engineering and executives, and lead how the domain uses AI-assisted and agentic development.
Job Description and Requirements
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.
Job Description and Requirements
What You’ll Do
- Design, build, and operate always-on, secure distributed systems with rigorous availability, throughput, and error SLOs that process more than a petabyte a month of unstructured data. Own how the systems behave under failure and load. Influence execution across engineering.
- Resolve the most complex, cross-organizational technical problems through deep technical expertise, collaboration, and hands-on implementation.
- Define and lead the organization-wide technical vision and architecture and shape long-term platform and data strategy.
- Establish enterprise standards for system scalability, reliability, maintainability, security, testability, and flexibility, partnering with teams to drive adoption.
- Influence and align engineering execution with company-level strategy and shape engineering culture across the organization.
- Influence executive-level product and platform decisions.
- Lead the evolution of Enrichment from primarily batch-oriented jobs toward streaming-first, continuously processing pipelines that deliver real-time and large-scale results (1K to 1B+ files), and write the code that proves the patterns out.
- Stay deeply hands-on. Principals at Relativity aren’t ivory-tower architects. They design, implement, review, and operate production software. You’ll be in the codebase, in the metrics, and owning systems end to end.
- Drive our agentic engineering push within Enrichment. Establish best practices, guardrails, and tooling for AI-assisted and agentic development, and raise the bar for how the domain designs, tests, and ships software in an AI-driven world.
What We’re Looking For
Required
- 12+ years of experience designing, building and operating complex cloud-native distributed systems.
- Experience building and operating systems held to strict availability, latency, and throughput SLOs, including 99.99% uptime and error budgets, where customers feel it immediately when something is down or wrong.
- Deep expertise in high-throughput data processing and transformation at scale, distributing work horizontally across a cluster: large batch pipelines, streaming/continuous systems, or both.
- Experience with durable workflow/orchestration engines (e.g., Temporal), event-driven architectures, and container-based compute (e.g., Kubernetes).
- Strong grounding in reliability, performance, security, and observability for services.
- Recognized authority in architecture and distributed systems.
- Experience defining organization-wide technical standards.
- Deep involvement in security, compliance, and reliability strategy.
- Ability to align technical vision with company-level strategy.
- Proven influence at senior and executive levels.
- Exceptional mentorship, communication, and strategic thinking skills.
Preferred
- Hands-on experience designing or scaling streaming / continuous data-processing systems (e.g., Event Hub, Kafka, Apache Spark, or similar stream-processing frameworks).
- Hands-on experience processing large volumes of raw, unstructured or semi-structured content such as documents, email, files, and media, not solely structured or transactional records.
- Experience with modern lakehouse and columnar processing at scale (e.g., Spark, Delta Lake, Iceberg, Parquet, Arrow).
- Background in legal tech, eDiscovery, search and information retrieval, security or observability platforms, or other high-scale regulated domains.
- Demonstrated leadership in adopting agentic and AI-assisted engineering workflows (e.g., GitHub Copilot, Cursor, or Claude Code) and establishing team best practices and guardrails.
- Experience guiding enterprise system or data architecture.
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.
- Scale That Matters: You’ll work on systems processing more than a petabyte of unstructured data per month, where the engineering problems are genuinely hard and the impact is immediate.
- 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:
$210,000 and $314,000
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:
Agile Methodology, Algorithms, Automation, Big Data Processing, Business Strategies, Cloud Based Services, Cloud Platform, Collaboration, Communication, Data Architecture Development, Data Systems, Distributed Systems, Distributed Systems Technologies, End-to-End Testing, Leadership, Mentorship, Problem Solving, Software Architectures, Strategic Planning, System Designs, Technical Leadership, Thought Leadership