Senior Manager, Software Engineering - AI
About The Position
NetDocuments is seeking a Senior Manager, Engineering to lead and scale its AI Search engineering team. The team develops embedding models and indexing pipelines that power semantic search across the NetDocuments platform, partnering with product and vertical teams to adapt capabilities to different use cases and industries. The role sets engineering vision and strategy for the AI Search platform and balances innovation with operational rigor. The Senior Manager reports to the Director of Engineering, AI and works closely with Product, Architecture, Data Science, and engineering teams. The position oversees delivery across multiple teams, develops engineering leaders and staff, and serves as a technical point of contact for AI Search. It also guides secure, compliant, high-performing search solutions while encouraging responsible experimentation and a collaborative, learning-oriented engineering culture.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field.
- At least 7 years of software engineering experience, including at least 3 years in engineering management roles.
- Demonstrated success managing multiple teams or a group of 7 or more engineers and leaders.
- Ability to define and execute a technical vision aligned with business strategy.
- Strong experience leading distributed, cloud-based product development using Azure or AWS.
- Familiarity with machine learning model deployment and lifecycle management, particularly embedding or NLP models.
- Experience building or owning large-scale data pipelines, 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, including navigating cross-team dependencies.
- Ability to synthesize complex technical information and present it effectively to leadership and cross-functional audiences.
Nice To Haves
- An 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 supports downstream LLM applications.
- Background in information retrieval or 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.
Responsibilities
- Shape and execute the long-term engineering strategy for the AI Search platform, focusing on embedding model quality, indexing pipeline reliability, and semantic relevance across verticals.
- Work with Product, Architecture, and vertical engineering teams to turn customer needs into scalable, production-ready search capabilities.
- Build and maintain a roadmap balancing model improvements, indexing infrastructure, and cross-team commitments.
- Oversee delivery across multiple teams to ensure high-quality, on-time releases.
- Manage and mentor engineers and technical staff, supporting hiring, performance management, and career development.
- Partner with vertical product and engineering teams to understand domain-specific search requirements and adapt semantic capabilities.
- Act as the technical point of contact for AI Search and explain tradeoffs involving relevance, latency, and model selection.
- Present technical strategies, roadmaps, and progress to senior leadership in business-focused terms.
- Drive engagement and communication across distributed teams and business units.
- Guide teams on embedding models, vector indexing, and semantic retrieval, while focusing on leadership 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 meet security, compliance, performance, privacy, and data residency standards.
- Promote responsible experimentation with emerging AI and retrieval technologies while maintaining production stability.
- Foster continuous learning, experimentation, collaboration, quality, innovation, transparency, open-source contributions, and knowledge sharing.
Benefits
- 90% of healthcare premiums covered by the company.
- Company HSA contribution.
- 401(k) match at 4% with immediate vesting.
- Flexible PTO, typically 3 to 4 weeks a year.
- 10 paid holidays.
- Monthly contributions for life activities and wellness.
- Access to LinkedIn Learning with monthly dedicated time to explore.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
