Advanced Software Engineer

Relativity•Illinois, IL

8d•$103,000 - $155,000

About The Position

As an Advanced Software Engineer at Relativity, you will independently take features from design to production in a cloud-based SaaS platform, using AI both as a development tool and as a product capability. You will write production C# and SQL and build the services, instrumentation, evaluation harnesses, and data pipelines that make Applied Science approaches reliable for customers and help diagnose problems when they arise. The team develops Case Strategy, a suite of applications that helps case teams define, validate, and present case strategies. The role contributes to the AI product Relativity aiR, which helps users analyze, organize, and understand case information. You will build and operate its AI systems at production scale, working with Applied Scientists, Product, and other engineering partners. The work spans databases, processing and web servers, search engines, clustering technologies, and other modern technologies.

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 CI/CD and understanding of DevOps principles.
At least 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, 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 and sound judgment about when to trust or verify their output.
Ability to design and document a component of a larger system, including non-functional requirements.
Ability to collaborate effectively with scientists, engineers, and product partners.

Nice To Haves

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, such as Terraform, Pulumi, AWS CDK, or CloudFormation.
Experience with MLflow or Kubeflow, or big data frameworks such as Apache Spark or Kafka.
Experience building or deploying models with 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.

Responsibilities

Build Relativity product offerings using object-oriented analysis, design, and programming, applying SOLID principles and design patterns across multiple languages.
Participate in the SCRUM process and deliver through CI/CD with strong observability.
Improve application and system performance at scale.
Troubleshoot issues, fix defects, and respond to client-specific problems.
Take prototypes or notebooks from Applied Science and independently turn them into deployed, 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 failure modes including drift, latency regressions, cost increases, tool-call and retrieval errors, and data-quality effects on outputs.
Build and maintain evaluation harnesses and regression checks that gate releases, expanding coverage as use cases grow.
Design components of AI solutions with senior review, document interfaces and non-functional requirements, and apply proven company patterns.
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, considering quality and cost.
Work with Relativity's security team to protect customer data and meet compliance requirements in AI features.
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 with the team, Applied Science, product managers, and the AI platform team.
Keep the team informed about AI innovations, learning opportunities, and future directions.