Manager, Software Engineering
NetDocuments · USA
About this role
## About NetDocuments NetDocuments is shaping the future of legal work—helping legal professionals spend less time searching for information and managing documents, and more time solving complex problems and delivering meaningful outcomes. We build 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 in legal technology, including our trusted intelligent document management platform and the legal context graph. ## 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’ll 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’ll partner closely with **Product, Architecture, and senior engineering leaders** to translate emerging AI technologies into meaningful product capabilities. ### Key Responsibilities - **Drive Engineering Delivery & Execution** - Plan and execute engineering initiatives to deliver high-quality AI capabilities predictably - Partner with Product and Architecture to deliver scalable, secure solutions - Balance feature development with reliability, performance, cost efficiency, and operational excellence - Identify technical risks, dependencies, and tradeoffs; communicate recommendations to leadership and stakeholders - Set clear priorities, accountability, and engineering practices - **Guide AI Technical Strategy & Architecture** - Partner with Principal and Staff Engineers on architectural decisions and implementation strategies - Evaluate AI model selection and tradeoffs (quality, latency, scalability, cost) - Guide prompt engineering and **retrieval-augmented generation (RAG)** approaches - Establish AI evaluation, testing, and monitoring expectations (including regression testing) - Ensure AI capabilities meet enterprise standards for security, privacy, compliance, and reliability - Use technical knowledge of **C#/.NET, microservices, containerization, and AWS or Azure** to remove blockers and support decisions - **Lead, Mentor & Develop Engineering Talent** - Coach and develop software engineers (performance, career growth, technical development) - Foster ownership, accountability, experimentation, and continuous improvement - Drive hiring and talent development - Encourage modern engineering practices and AI-assisted development tools - Enable effective collaboration and continuous technical improvement - **Drive Cross-Functional Collaboration & Alignment** - Align technical priorities with Product, Design, Architecture, and other AI engineering teams - Communicate progress, decisions, risks, and tradeoffs clearly to stakeholders and senior leadership - Translate complex technical concepts into business outcomes and recommendations ## What You’ll Need to Be Successful - **6+ years** professional software engineering experience, including **2+ years** managing engineering teams - Experience delivering **production-grade AI / LLM-powered features** in an enterprise SaaS environment - Strong understanding of **LLMs** (prompt engineering, RAG, context limitations, latency, cost, failure modes) - Familiarity with **AI evaluation** methodologies and retrieval systems - Understanding of AI ag
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