Posting Type
Hybrid/Remote
Job Overview
ABOUT THE ROLE
As an Advanced Software Engineer on the Discovery team, you will design, build, and operate the next generation of AI-driven, scalable, high-performance systems that process large volumes of data. This role combines deep technical expertise with a collaborative mindset to solve complex challenges while delivering secure, cloud-native solutions.
Job Description and Requirements
WHAT YOU’LL DO
- Build and operate distributed search ingestion pipelines using Elasticsearch, including index lifecycle management (ILM), shard capacity planning, and rollover policies at scale across large workspace environments
- Build and maintain message-based consumer services for high-volume document ingestion with robust failure handling, retry policies, and observability
- Partner with architects and tech leads to implement cloud-native solutions on Azure using containerization technologies such as Docker and Kubernetes along with modern CI/CD workflows
- Drive reliability improvements, including pre-flight capacity checks, error classification, and automated recovery from cluster-level failures
- Contribute to team quality through pair programming, code reviews, and clear technical documentation
- Champion automated testing, static analysis, observability, and DevOps practices to ensure performance and reliability
- Collaborate with senior engineers and architects in design sessions and elevate team engineering practices
- Use AI-assisted coding tools to accelerate development and reduce boilerplate work
- Build tools and automation to streamline workflows across engineering disciplines
- Collaborate with product managers and engineers to deliver high-quality features
WHAT WE’RE LOOKING FOR
Required
- Bachelor’s degree in Computer Science, Engineering, or related field OR equivalent experience
- 3+ years of experience in software engineering with a focus on distributed systems
- Proficiency in programming languages such as C#, Java, or Python
- Experience with cloud platforms (e.g., Azure, AWS) and containerization technologies
- Strong understanding of software design principles and performance optimization
- Ability to work collaboratively in a team environment and communicate effectively
Preferred
- Experience with Elasticsearch, including index templates, ILM policies, bulk API, shard management, and cluster capacity planning
- Familiarity with message-based or event streaming platforms for building high-throughput, reliable data pipelines
- Experience with big data technologies such as Spark
- Familiarity with CI/CD pipelines and DevOps practices
- Knowledge of observability tools and best practices for system reliability
WHY WE COULD BE A GREAT FIT
Impactful Mission
- Build systems that help customers organize data, discover the truth, and act on it in high-stakes legal matters.
Engineering at Scale
- Work on distributed, cloud-native systems that process large volumes of data.
Cutting-Edge Technology
- Build with AI, cloud platforms, and scalable architectures shaping legal tech.
Growth and Ownership
- Gain experience owning systems end-to-end across cloud and distributed environments.
Collaborative Culture
- Work in a team focused on knowledge sharing and continuous improvement.
Inclusive Environment
- Diverse perspectives create stronger teams and better outcomes.
Compensation and Benefits
- Competitive salary, benefits, DTO, parental leave, and 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 betweenfollowing 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
