Senior Manager, Software Engineering - AI

NetDocuments is hiring a Senior Manager to lead and scale its AI Search engineering team. The role sets engineering strategy, oversees embedding models and indexing pipelines, develops engineering leaders, and partners across product, architecture, and data science to deliver secure, enterprise-grade semantic search capabilities.

Responsibilities:

• Lead and scale our AI Search engineering team as we build next generation intelligent search capabilities that transform how legal professionals find and surface critical content
• Shape and execute the long term engineering strategy for the AI Search platform, with a focus on embedding model quality, indexing pipeline reliability, and semantic relevance across verticals
• Collaborate with Product, Architecture, and vertical engineering teams to translate customer needs into scalable, production ready search capabilities
• Build and maintain a robust roadmap that balances platform investments in model improvements and indexing infrastructure with cross team partnership commitments
• Oversee delivery execution across multiple teams to ensure high quality, on time releases
• Manage and mentor Engineers and Technical staff, fostering a culture of trust, collaboration, and continuous improvement
• Guide hiring, performance management, and career development to build diverse, high impact teams
• Create an environment that attracts top engineering talent and empowers them to deliver their best work
• Partner with vertical product and engineering teams to understand domain specific search requirements and adapt semantic capabilities accordingly
• Serve as the technical point of contact for AI Search capabilities, helping stakeholders understand tradeoffs in relevance, latency, and model selection
• Present technical strategies, roadmaps, and progress to senior leadership in clear, business focused terms
• Drive engagement and communication across distributed teams and business units
• Maintain strong working knowledge of embedding models, vector indexing, and semantic retrieval while focusing on guiding teams rather than day to day coding
• Champion best practices for model lifecycle management, indexing pipeline design, relevance evaluation, and scalable architecture
• Ensure AI Search solutions are designed securely and meet compliance, performance, privacy, and data residency standards
• Promote responsible experimentation with emerging AI and retrieval technologies, balancing innovation with production stability
• Foster a growth mindset, continuous learning, and experimentation within the engineering organization
• Cultivate a collaborative engineering culture that values quality, innovation, and transparency
• Encourage contributions to open source projects and knowledge sharing across the company

Requirements:

• Bachelor's degree in Computer Science, Engineering, or related field
• 7+ years of software engineering experience, including 3+ years in engineering management roles
• Demonstrated success managing multiple teams or a group of 7+ engineers and leaders
• Proven ability to define and execute a technical vision in alignment with business strategy
• Strong experience leading distributed, cloud based product development (Azure or AWS)
• Familiarity with machine learning model deployment and lifecycle management, particularly embedding or NLP models
• Experience building or owning data pipelines at scale including indexing, transformation, or ETL workflows
• Deep understanding of modern engineering practices including CI/CD, microservices, and scalable architectures
• Excellent stakeholder management and executive communication skills, with experience navigating cross team dependencies
• Ability to synthesize complex technical information and present it effectively to leadership and cross functional audience
• advanced degree
• Hands on experience with semantic search or dense vector retrieval including embedding model selection, or hybrid search
• Experience with Elasticsearch or OpenSearch
• Familiarity with retrieval augmented generation (RAG) pipelines and how search quality feeds downstream LLM applications
• Background in information retrieval, natural language processing
• Experience adapting a shared platform capability across multiple product verticals or customer segments
• A history of building high performing, engaged teams that deliver impactful software