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Relativity

Cloud-based e-discovery platform for legal

Advanced Software Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeIllinois, USA

About the Job

Requirements

  • At least 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 continuous integration and continuous delivery (CI/CD) and understanding of DevOps principles.
  • At least 1 year building or operating AI/ML systems or their data pipelines, such as large language model (LLM) integrations, prompt design, retrieval-augmented generation (RAG), or embeddings.
  • Experience deploying and monitoring models or LLM-based services in a cloud environment.
  • Practical machine learning fluency, including interpreting evaluation results, reasoning about model failure modes, and making quality, latency, and cost trade-offs.
  • Experience building data pipelines with orchestration tooling such as Prefect or Airflow, with attention to reproducibility.
  • Working knowledge of Python alongside C#.
  • Regular use of AI-assisted development tools, with judgment about when to trust and verify their output.
  • Ability to design and document a component of a larger system, including non-functional requirements.
  • Preferred qualifications include experience building evaluation harnesses or regression suites for AI systems, including evaluating LLM output quality.
  • Preferred qualifications include experience with LLM orchestration or agent frameworks, agentic workflows, and tool calling.
  • Preferred qualifications include experience with large-scale or sensitive data.
  • Preferred qualifications include experience with Azure DevOps and Azure AI and data services.
  • Preferred qualifications include experience with Docker, Kubernetes, and Helm.
  • Preferred qualifications include experience with infrastructure as code, such as Terraform, Pulumi, AWS CDK, or CloudFormation.
  • Preferred qualifications include experience with MLflow or Kubeflow, or big data frameworks such as Apache Spark or Kafka.
  • Preferred qualifications include experience building or deploying models with PyTorch, TensorFlow, or Keras, or depth in an area such as natural language processing.
  • Preferred qualifications include a Bachelor's or advanced degree in Computer Science, Computer Engineering, Mathematics, Statistics, or Artificial Intelligence.
  • Required skills listed include engineering principles, hardware integration, innovation, problem solving, process improvements, quality assurance, research and development, system designs, technical documents, and troubleshooting.

Responsibilities

  • Build the primary product offering using object-oriented analysis, design, and programming with SOLID principles and design patterns in multiple languages.
  • Participate in the Scrum process and deliver through CI/CD with strong observability.
  • Improve application and system performance at scale.
  • Troubleshoot issues by fixing defects and responding to client-specific problems.
  • Independently take prototypes or notebooks from Applied Science through deployment as monitored production services delivered through CI/CD.
  • Instrument models and prompts for quality, latency, and cost, and build dashboards and alerts against reliability targets.
  • Diagnose and mitigate common failure modes, including drift, latency regressions, cost increases, tool-call and retrieval errors, and data-quality effects on outputs.
  • Build and maintain the evaluation harness and regression checks that gate releases, extending coverage as use cases grow.
  • Design components of AI solutions with senior review, document interfaces and non-functional requirements, and apply patterns proven elsewhere in the company.
  • Build and operate feature data pipelines with reproducibility, lineage, and automated data-quality monitoring.
  • Make and document implementation trade-offs, including batching, caching, model tier, timeouts, and fallbacks, with reasoning about quality and cost.
  • Work with the security team to protect customer data and meet compliance requirements in every AI feature built.
  • Use modern AI coding tools in daily design, development, testing, and code review, and share effective practices with the team.
  • Prioritize independently across competing tasks and deliver predictably.
  • Mentor L3 engineers and collaborate across the team and with Applied Science, product managers, and the AI platform team.
  • Keep the team informed about AI innovations, learning opportunities, and future directions.

About the Company

Relativity

Cloud-based e-discovery platform for legal

Relativity is a tech company that provides e-discovery software through a cloud-based platform called RelativityOne. It helps corporations, law firms, and government agencies identify, collect, and produce electronically stored information (ESI) for legal cases, investigations, and regulatory compliance. The platform guides users through all phases of e-discovery: legal hold, data collection, early case assessment, processing, review, production, and analytics, using a subscription model and optional custom integrations via the Relativity App Hub. The company differentiates itself with an end-to-end, cloud-based solution that supports a broad ecosystem of integrations, along with a strong emphasis on community learning and ongoing training. Its goal is to enable organizations to manage and analyze large data volumes efficiently for legal and regulatory purposes while fostering inclusion and giving back to the community.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$845M
Headquarters
Chicago, IL
Founded
2001

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