Senior Manager - Software Engineering, AI
$190k - $215k
Senior
Bachelor's
Remote in USA+1 moreMore locations: Lehi, UT, USA
Remote
Engineering ManagementEngineering Leadership
About the job
Requirements
- A bachelor's degree in Computer Science, Engineering, or a related field is required; an advanced degree is preferred.
- 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.
- Experience leading distributed, cloud-based product development using Azure or AWS.
- Familiarity with machine learning model deployment and lifecycle management, particularly embedding or natural language processing models.
- Experience building or owning data pipelines at scale, including indexing, transformation, or extract, transform, and load workflows.
- Deep understanding of modern engineering practices, including continuous integration and continuous delivery, microservices, and scalable architectures.
- Experience managing stakeholders and communicating with executives while navigating cross-team dependencies.
- Ability to synthesize complex technical information and present it effectively to leadership and cross-functional audiences.
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.
- Collaborate with Product, Architecture, and vertical engineering teams to translate customer needs into scalable, production-ready search capabilities.
- Build and maintain a roadmap that balances platform investments in model improvements and indexing infrastructure with cross-team partnership commitments.
- Oversee delivery across multiple teams to ensure high-quality, on-time releases.
- Manage and mentor engineers and technical staff, fostering trust, collaboration, and continuous improvement.
- Guide hiring, performance management, and career development to build diverse, high-impact teams.
- Create an environment that attracts engineering talent and empowers teams to deliver their best work.
- Partner with vertical product and engineering teams to understand domain-specific search requirements and adapt semantic capabilities.
- Serve as the technical point of contact for AI Search capabilities, explaining 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 working knowledge of embedding models, vector indexing, and semantic retrieval while guiding teams rather than coding day to day.
- 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 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.
Desired Qualifications
- 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 pipelines and how search quality supports downstream large language model 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.
About the company
NetDocuments provides a cloud-based document and email management platform for legal and professional services. It uses a subscription SaaS model to offer secure storage, compliance, and features like enterprise search and real-time collaboration, with integrations to Outlook and Microsoft Office. It differentiates itself by offering a single source of truth with rapid security validation, governance, and strong integrations that reduce administrative tasks. Its goal is to help customers manage information securely and efficiently so users can focus on higher-value work.
Company Size
501-1,000
Company Stage
Late Stage VC
Total Funding
$30M
Headquarters
Lehi, Utah
Founded
1999
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Simplify's Take
What believers are saying
- October 1, 2026 brought Cody Crnkovich to deepen partner-led distribution.
- September 2026 ChatGPT plugin and August Gemini Enterprise launch widen AI discovery.
- August 2026 Tabular Review, Legal Authorities, and Inc. 5000 recognition reinforce momentum.
What critics are saying
- iManage, Harvey, and Legora bundle workflow AI, eroding NetDocuments' integration moat by 2027.
- OpenAI and Google control model distribution, squeezing NetDocuments into a feature layer.
- eDOCS support and migration complexity can slow sales and trigger integration failures through 2027.
What makes NetDocuments unique
- Cloud-native DMS built for legal since inception, not a migrated on-prem suite.
- Legal Context Graph turns firm documents, matters, and citations into reusable AI memory.
- 150-plus integrations plus eDOCS acquisition expand reach across law firms and public sector.
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Benefits
- Health Insurance
- 401(k) Retirement Plan
- Flexible PTO
- Paid Holidays
- HSA company contribution
- 401(k) Company Match
- Wellness Program
- Phone/Internet Stipend
- LinkedIn Learning access