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Manager, Software Engineering

AI Summary
NetDocuments is hiring an Engineering Manager to lead a team building shared AI capabilities for its enterprise legal-technology platform. The manager will own delivery planning, technical direction, engineering quality, and talent development while partnering closely with Product, Architecture, and senior engineering leaders. The role requires practical expertise in enterprise LLM features, including RAG, prompt engineering, model evaluation, monitoring, latency, security, and cost trade-offs. Candidates need a strong software engineering background in cloud-native distributed systems, .NET or similar backend technologies, microservices, containers, and AWS or Azure. This is a senior technical leadership role serving a regulated SaaS environment and balancing product velocity with reliability and compliance.
Remote from
USA
Salary
USD 170k–190k / yr
Employment
Full Time
Experience
Senior
Published
Apply before
7 Dec 2026
Listing views
45
Application actions
1
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Opportunity details

About this 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).
  • Strong technical foundation in modern software engineering, including distributed systems, microservices, and cloud-native architectures.
  • Experience with cloud platforms such as AWS or Azure and modern engineering practices including CI/CD, containerization, and observability.
  • Working knowledge of C#/.NET or similar backend development technologies, with the ability to evaluate technical designs and guide engineering decisions.
  • Demonstrated ability to lead engineering teams, manage competing priorities, and deliver complex technical initiatives.
  • Strong communication, collaboration, and stakeholder management skills, with the ability to influence technical and business decisions.
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

What Will Make You Stand Out

  • Experience developing AI-powered solutions within legal technology, document management, or other regulated industries.
  • Experience building and scaling document AI capabilities, including intelligent document processing and retrieval systems.
  • Experience evaluating and managing AI model providers, including performance, cost optimization, and vendor selection.
  • Familiarity with model customization techniques such as fine-tuning and the ability to evaluate their business and technical value.
  • Experience leading teams responsible for shared AI services or platform capabilities used across multiple products.
  • Proven success building high-performing engineering teams that consistently deliver impactful software.
  • Advanced degree in Computer Science, Engineering, or a related field.

What You’ll Love About NetDocuments

  • The People!
  • 90% healthcare premiums company covered
  • HSA company 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 & wellness
  • Access to LinkedIn Learning with monthly dedicated time to explore
  • Connection, access, and mentorship from exceptional leaders
  • Growing company with opportunities for advancement
  • Authenticity and accountability from leadership

Compensation Transparency

The compensation range for this position is: $170,000 – $190,000

The posted cash compensation for this position includes on target earnings. Some roles may qualify for overtime pay. Individual compensation packages are determined based on various factors specific to each candidate, such as career level, skills, experience, geographic location, qualifications, and other job-related considerations.

Equal Opportunity

NetDocuments is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. All employment decisions are based on business needs, job requirements, individual qualifications, without regard to race, color, religion, sex, (including pregnancy), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity and/or expression, military and veteran status, or any other status protected by laws or regulations in the locations where we operate. NetDocuments believes diversity and inclusion among our employees is critical to our success, and we are committed to providing a work environment free of discrimination and harassment.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThe position combines people management with technical leadership for production AI systems in a security- and compliance-sensitive legal SaaS product. It requires making complex architectural and model trade-offs while delivering predictable outcomes across multiple stakeholders.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$180,000
US market range (per year)$175k–$215k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses cash compensation of $170,000–$190,000 USD. The annual cadence is inferred from the compensation amount, US location, and senior full-time engineering management context; the posting does not explicitly state a pay period. Estimated US market compensation for a comparable Engineering Manager leading enterprise AI platform work is $175,000–$215,000 USD per year.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you evaluate whether an LLM-powered RAG capability is ready for enterprise production use?

I would define task-specific quality metrics such as groundedness, retrieval relevance, answer correctness, and safety, then build representative evaluation sets from real user workflows. I would combine automated regression tests with human review, monitor latency, cost, failure patterns, and adoption after launch, and establish release gates for model, prompt, and retrieval changes.

Describe how you balance rapid AI feature delivery with security, privacy, and reliability requirements.

I establish non-negotiable engineering guardrails early, including data classification, access controls, auditability, evaluation criteria, and operational ownership. I then use phased releases, feature flags, observability, and clear risk reviews so the team can learn quickly without exposing customers or the platform to unacceptable risk.

How would you help a team choose among AI model providers or model configurations?

I would start with the user outcome and constraints, then compare candidates against quality, latency, throughput, cost, data-handling requirements, availability, and operational maturity. I would use controlled benchmarks and production-like workloads, document the trade-offs, and design abstraction and fallback strategies to avoid unnecessary vendor lock-in.

How do you manage competing priorities across product delivery, platform reliability, and technical debt?

I make capacity and trade-offs visible through a shared planning process that includes product, architecture, and engineering. I reserve explicit investment for reliability and debt, quantify customer and operational risk where possible, and communicate the consequences of deferring foundational work so prioritization decisions are deliberate.

What is your approach to developing and retaining a high-performing engineering team?

I set clear expectations, connect individual work to customer and business outcomes, and provide frequent actionable feedback. I create growth plans tailored to each engineer, delegate meaningful ownership, recognize impact, and foster an environment where experimentation, constructive challenge, and accountability are expected.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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