Manager, Software Engineering
Lehi, UT, United States2h ago
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Key details
- Location
- Lehi, UT, United States
- Work style
- Remote
- Level
- Senior
- Experience
- 6–9 yrs
- Function
- Software engineering
- Focus area
- Backend
- Posted
- 2h ago
Skills
About the role
NetDocuments is committed to providing an excellent candidate experience and will never ask you to engage in recruitment activity without phone, video, and in person meetings and communications from emails using the @netdocuments.com domain. If you have any concerns or questions about communications you have received, please send them to hrgroup@netdocuments.com so our team members can review.
About NetDocuments
At NetDocuments, we're shaping the future of legal work. We believe legal professionals should spend less time searching for information and managing documents, and more time solving complex problems, serving clients, and delivering meaningful outcomes. That's why we're building technology that helps organizations work smarter, collaborate more effectively, and unlock the full value of their institutional knowledge.
Our team is redefining what's possible for legal technology. NetDocuments is the trusted intelligent document management platform for legal professionals and the company behind the industry's first and only legal context graph—a breakthrough that gives legal professionals and AI a richer understanding of how matters, documents, people, and knowledge connect across an organization while respecting enterprise-grade security, governance, permissions, and ethical walls.
Innovation is only part of our story. We believe our greatest strength is our people. We foster a collaborative, inclusive, and high-performing culture where curiosity is encouraged, diverse perspectives are valued, and employees are empowered to make a meaningful impact. Whether you're building products, serving customers, or supporting the business, your work helps shape the future of one of the world's most trusted legal technology platforms.
That commitment to our employees and customers has earned us recognition as one of the nation's top workplaces, including:
- Four consecutive appearances on the Inc. 5000 list of America's Fastest-Growing Private Companies
- Five-time Top Workplace USA winner
- Five-time Salt Lake Tribune Top Workplace
- Multiple Top Workplaces Culture Excellence awards recognizing innovation, employee appreciation, work-life flexibility, and compensation & benefits
If you're excited to solve meaningful challenges, work alongside talented colleagues, and help define the next generation of legal technology, we'd love to meet you.
What You’ll Do
NetDocuments is seeking an Engineering Manager to lead a team responsible for building and delivering shared AI capabilities across our platform. In this role, you will drive engineering execution, guide technical direction, and lead the development of scalable, secure, and reliable AI-powered solutions that enhance how legal professionals work.
You will partner closely with Product, Architecture, and senior engineering leaders to translate emerging AI technologies into meaningful product capabilities. This is a technical leadership role focused on driving delivery, developing engineering talent, and ensuring our AI solutions meet the highest standards of quality, performance, and enterprise readiness.
You will:
Drive Engineering Delivery & Execution
- 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.
Guide AI Technical Strategy & Architecture
- 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 (RAG) 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.
- Leverage technical knowledge of C#/.NET, microservices, containerization, and AWS or Azure to evaluate designs, remove blockers, and support engineering decisions.
Lead, Mentor & Develop Engineering Talent
- 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.
Drive Cross-Functional Collaboration & Alignment
- 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.
What You’ll Need to Be Successful
- 6+ years of professional software engineering experience, including 2+ years managing engineering teams.
- Experience delivering production-grade AI or LLM-powered features within an enterprise SaaS environment.
- Strong understanding of large language models (LLMs), including prompt engineering, retrieval-augmented generation (RAG), 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 emerging integration standards such as Model Context Protocol (MCP).