Our team is the driving force behind Case Strategy, a comprehensive suite of applications designed to empower case teams in constructing winning cases. By seamlessly integrating with Relativity, Case Strategy allows users to quickly and easily define, validate, and present their case strategies. Our team owns the flagship AI product that significantly reduces the time and effort needed to analyze, organize, and understand case information, enhancing attorney productivity and case management. We are proud to be one of the few teams at Relativity leveraging AI to innovate our products, making us a leader in the legal tech space.
You will build and operate the AI systems behind Relativity aiR at production scale, under real legal stakes. You will work side by side with Applied Scientists, who own the science, and with Product, who owns the value case, so that what we ship meets the reliability target it was promised at. Along the way you will work with multiple databases, processing and web servers, search engines, and clustering technologies, using many of the newer and stronger technologies available.
Responsibilities
Core software engineering
Product Development. Build our primary product offering, Relativity, using object-oriented analysis, design, and programming with SOLID principles and design patterns in multiple languages.
Agile Delivery. Participate in our SCRUM process and deliver through CI/CD with strong observability.
Performance. Improve application and system performance at scale.
Quality and Support. Troubleshoot issues by fixing defects and responding to client-specific problems.
AI engineering
Prototype to Production. Independently take a prototype or notebook from Applied Science to a deployed, monitored production service, delivered through CI/CD.
Instrument. Instrument models and prompts for quality, latency, and cost, and build dashboards and alerts against the reliability target.
Diagnose. Diagnose and mitigate common failure modes, including drift, latency regressions, cost blow-ups, tool-call and retrieval errors, and data-quality effects on outputs.
Evaluation Harness. Build and maintain the evaluation harness and regression checks that gate releases, and extend coverage as use cases grow.
Component Design. Design components of an AI solution with senior review, document interfaces and non-functional requirements, and apply patterns proven elsewhere in the company.
Data Pipelines. Build and operate the pipelines for a feature with reproducibility, lineage, and automated data-quality monitoring.
Trade-offs. Make and document implementation trade-offs (batching, caching, model tier, timeouts, fallbacks) with sound reasoning about quality and cost.
Security and Compliance. Work with Relativity's security team to protect customer data and meet compliance requirements in every AI feature you build.
AI-Assisted Development. Use modern AI coding tools in your daily work to raise the speed and quality of design, development, testing, and code review, and share what works with the team.
Collaboration and growth
Prioritize. Prioritize independently across competing tasks and deliver predictably.
Mentor and Collaborate. Mentor L3 engineers, and collaborate across the team and with Applied Science, product managers, and the AI platform team.
Communication. Keep your team informed about AI innovations, learning opportunities, and future directions.
Required Qualifications
3+ years of professional software development experience using C# and Microsoft SQL Server, or related object-oriented languages.
Experience building web applications with JavaScript and ASP.NET.
Experience building scalable solutions on Azure or another cloud platform.
Experience working on an agile software development team.
Experience with CI/CD and an understanding of DevOps principles.
1+ year building or operating AI/ML systems or their data pipelines, such as LLM integrations, prompt design, retrieval-augmented generation (RAG), or embeddings.
Experience deploying and monitoring models or LLM-based services in a cloud environment.
Practical ML fluency: you can read evaluation results, reason about model failure modes, and make quality, latency, and cost trade-offs.
Experience building data pipelines with orchestration tooling (such as Prefect or Airflow) and attention to reproducibility.
Working knowledge of Python alongside C#.
Regular use of AI-assisted development tools, with sound judgment about when to trust and when to verify their output.
Ability to design and document a component of a larger system, including non-functional requirements.
Effective collaboration with scientists, engineers, and product partners.
Preferred Qualifications
Experience building evaluation harnesses or regression suites for AI systems, including evaluating LLM output quality.
Experience with LLM orchestration or agent frameworks, agentic workflows, and tool calling.
Experience with large-scale or sensitive data.
Experience with Azure DevOps and Azure AI and data services.
Experience with Docker, Kubernetes, and Helm.
Experience with infrastructure as code (for example Terraform, Pulumi, AWS CDK, or CloudFormation).
Experience with MLflow or Kubeflow, or with big data frameworks such as Apache Spark or Kafka.
Experience building or deploying models with frameworks such as PyTorch, TensorFlow, or Keras, or depth in an area such as NLP.
Bachelor's or advanced degree in Computer Science, Computer Engineering, Mathematics, Statistics, or Artificial Intelligence.
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, which accelerates 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 and Benefits. Competitive salary, health and retirement programs, wellness resources, discretionary time off (DTO), parental leave for primary and secondary caregivers, two annual company breaks, a 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
