Lead .NET Engineer - Automation Services

Relativity is a leading legal data intelligence company building AI-powered, cloud-native technology to help users organize data and gain actionable insights for high-stakes legal work. The company serves the world’s largest law firms, corporations, and government agencies with its RelativityOne platform.

• 7+ years of software development experience with strong expertise in C# and .NET
• Deep experience with Microsoft Azure, including networking, compute, identity, and automation
• Proven ability to lead technical projects and set architectural direction
• Hands-on experience with Infrastructure as Code (e.g., Terraform, Bicep) and CI/CD automation
• Strong understanding of containers, Kubernetes, and modern DevOps practices
• Strong communication and collaboration skills across engineering, product, and leadership teams
• Experience mentoring engineers and supporting technical growth within a team

Nice to have:

• Experience implementing AI/ML tools or practices within developer platforms or infrastructure

• Lead the design and implementation of platform services, infrastructure automation, and development tooling using .NET and Azure
• Define and evolve architectural patterns and standards for cloud-native development, CI/CD, and Infrastructure as Code
• Collaborate with Engineering Managers, Staff Engineers, Principal Engineers, and Architects to align platform strategy with business and technical priorities
• Mentor engineers through design reviews, code feedback, and technical guidance
• Identify system-level improvements and lead initiatives to enhance developer productivity, platform resilience, and operational efficiency
• Promote DevOps practices, automation, and observability across the engineering organization
• Drive adoption of AI/ML capabilities where they improve developer experience or platform efficiency
• Foster a culture of ownership, experimentation, and rapid delivery with a focus on engineering excellence
• Stay current with industry trends and continuously improve tools, practices, and technical decision-making