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NetDocuments

Cloud-based document management for legal

Manager Software Engineering

Engineering LeadershipPosted on Nov 6
Full-timeRemote

About the Job

Requirements

  • At least 6 years of professional software engineering experience, including at least 2 years managing engineering teams.
  • Experience delivering production-grade AI or large language model-powered features in an enterprise software-as-a-service environment.
  • Strong understanding of large language models, including prompt engineering, retrieval-augmented generation, context limitations, latency, cost considerations, and common failure modes.
  • Familiarity with AI evaluation methodologies, retrieval systems, and approaches for measuring model accuracy, reliability, and performance.
  • Understanding of AI agent architectures, tool-calling patterns, and integration standards such as Model Context Protocol.
  • Strong technical foundation in modern software engineering, including distributed systems, microservices, and cloud-native architectures.
  • Experience with cloud platforms such as Amazon Web Services or Azure and modern engineering practices including continuous integration/continuous delivery, containerization, and observability.
  • Working knowledge of C#/.NET or similar backend development technologies, with the ability to evaluate technical designs and guide engineering decisions.
  • Demonstrated ability to lead engineering teams, manage competing priorities, and deliver complex technical initiatives.
  • Strong communication, collaboration, and stakeholder management skills, with the ability to influence technical and business decisions.
  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Responsibilities

  • Lead the planning and execution of engineering initiatives, ensuring predictable delivery of high-quality AI capabilities.
  • Partner with Product and Architecture to translate customer needs and emerging AI technologies into scalable, secure solutions.
  • Balance feature development with system reliability, performance, cost efficiency, and operational excellence.
  • Proactively identify technical risks, dependencies, and tradeoffs, communicating recommendations to leadership and cross-functional stakeholders.
  • Establish clear priorities, accountability, and engineering practices that support consistent delivery.
  • Partner with Principal and Staff Engineers to guide architectural decisions, technical direction, and implementation strategies for AI-powered solutions.
  • Evaluate AI model selection and technical tradeoffs, including response quality, latency, scalability, and cost.
  • Guide the development of prompt engineering and retrieval-augmented generation approaches to deliver accurate, contextually relevant AI experiences.
  • Establish expectations for AI evaluation, testing, and monitoring, including regression testing for model and prompt changes.
  • Ensure AI capabilities meet enterprise standards for security, privacy, compliance, and reliability.
  • Use technical knowledge of C#/.NET, microservices, containerization, and Amazon Web Services or Azure to evaluate designs, remove blockers, and support engineering decisions.
  • Lead, coach, and develop a team of software engineers, supporting performance, career growth, and technical development.
  • Foster a culture of ownership, accountability, experimentation, and continuous improvement.
  • Drive hiring and talent development efforts to build a high-performing engineering team.
  • Encourage the adoption of modern engineering practices and AI-assisted development tools to improve productivity and software quality.
  • Create an environment where engineers collaborate effectively, challenge assumptions, and continuously improve technical solutions.
  • Partner with Product, Design, Architecture, and other AI engineering teams to align technical priorities and shared platform capabilities.
  • Communicate engineering progress, technical decisions, risks, and tradeoffs clearly to stakeholders and senior leadership.
  • Build strong cross-functional relationships that support efficient decision-making and successful product delivery.
  • Translate complex technical concepts into clear business outcomes and recommendations.

Desired Qualifications

  • Experience developing AI-powered solutions within legal technology, document management, or other regulated industries.
  • Experience building and scaling document AI capabilities, including intelligent document processing and retrieval systems.
  • Experience evaluating and managing AI model providers, including performance, cost optimization, and vendor selection.
  • Familiarity with model customization techniques such as fine-tuning and the ability to evaluate their business and technical value.
  • Experience leading teams responsible for shared AI services or platform capabilities used across multiple products.
  • Proven success building high-performing engineering teams that consistently deliver impactful software.
  • Advanced degree in Computer Science, Engineering, or a related field.

About the Company

NetDocuments

Cloud-based document management for legal

NetDocuments offers a cloud-based document and email management platform for legal and professional services. It operates as a subscription-based SaaS, providing secure storage, retrieval, and governance with features like enterprise search and real-time collaboration (ndThread, SetBuilder) integrated with Outlook and Microsoft Office. It differentiates itself by focusing on legal and professional services, delivering a single source of truth with rapid security validation and strong governance, plus tight integrations to streamline workflows. Its goal is to help customers manage information securely and efficiently, reduce admin time, and let users focus on higher-value work.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$30M
Headquarters
Lehi, UT
Founded
1999

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