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# Senior Manager, Software Engineering – AI

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[Apply for this job](#job-application)[View company](https://jobicy.com/company/netdocuments.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 190k–215k / yrDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceDirectorPublished23 Oct 2026Apply before22 Nov 2026Listing views35Application actions2Application toolkit

## Make your next move.

Prepare your resume, explore your fit, and draft a cover letter for this opportunity.

AI Summary

## The role, at a glance.

NetDocuments seeks a senior engineering leader to scale its AI Search platform for legal-technology use cases. The role leads multiple engineers and technical leaders responsible for embedding models, vector indexing, semantic retrieval, and reliable indexing pipelines. It combines long-term platform strategy, delivery oversight, talent development, and stakeholder management across Product, Architecture, Data Science, and vertical engineering teams. Success requires strong cloud-product leadership, practical knowledge of NLP and retrieval systems, and the ability to communicate technical trade-offs to senior leaders. The position is remote within the United States and reports to the Director of Engineering, AI.

## Role DNA

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

### Job Complexity

5/5EasyHard

### Pace & Pressure

5/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThis is a senior people-and-platform leadership role spanning several teams, enterprise AI-search architecture, operational quality, and cross-functional delivery. It requires depth in semantic retrieval and ML lifecycle practices alongside executive-level communication and organizational leadership.

## Salary analysis

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

Estimated job median (per year)Market rate$202,500US market range (per year)$185k–$235k0$258.50k

AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a cash compensation range of $190,000–$215,000 USD. The posting does not state a pay cadence, so yearly compensation is inferred from the amount, seniority, US location, and standard full-time professional compensation conventions. Estimated US market compensation for a senior engineering manager leading AI search is $185,000–$235,000 USD per year.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Engineering leadership](https://jobicy.com/jobs?search_keywords=Engineering%20leadership.md)[Semantic search](https://jobicy.com/jobs?search_keywords=Semantic%20search.md)[Vector indexing](https://jobicy.com/jobs?search_keywords=Vector%20indexing.md)[Embedding models](https://jobicy.com/jobs?search_keywords=Embedding%20models.md)[Information retrieval](https://jobicy.com/jobs?search_keywords=Information%20retrieval.md)[Natural language processing](https://jobicy.com/jobs?search_keywords=Natural%20language%20processing.md)[Retrieval-augmented generation](https://jobicy.com/jobs?search_keywords=Retrieval-augmented%20generation.md)[Elasticsearch](https://jobicy.com/jobs?search_keywords=Elasticsearch.md)[OpenSearch](https://jobicy.com/jobs?search_keywords=OpenSearch.md)[Machine learning lifecycle management](https://jobicy.com/jobs?search_keywords=Machine%20learning%20lifecycle%20management.md)[Data pipelines](https://jobicy.com/jobs?search_keywords=Data%20pipelines.md)[Cloud architecture](https://jobicy.com/jobs?search_keywords=Cloud%20architecture.md)[CI/CD](https://jobicy.com/jobs?search_keywords=CICD.md)[Stakeholder management](https://jobicy.com/jobs?search_keywords=Stakeholder%20management.md)[Technical strategy](https://jobicy.com/jobs?search_keywords=Technical%20strategy.md)

Sample interview questionsHow would you set a technical strategy for an AI Search platform that serves multiple product verticals?I would begin with shared customer and business outcomes, then define platform capabilities that can be reused across verticals, such as embedding services, indexing standards, evaluation tooling, and access-control integration. I would prioritize investments through a roadmap that balances reliability, relevance improvements, and vertical-specific needs, with measurable quality and latency targets.

How do you evaluate semantic-search quality and decide when to change an embedding model?

I use a representative, versioned evaluation set combining offline relevance judgments, production query analysis, and segment-level metrics. A model change should demonstrate meaningful gains in metrics such as recall, ranking quality, latency, and cost, while preserving security and data-residency requirements through staged experiments and monitored rollout.

Describe how you would improve the reliability of a large-scale indexing pipeline.

I would establish clear service-level objectives for freshness, completeness, throughput, and recovery time, then instrument every stage of ingestion, transformation, embedding, and indexing. I would design for idempotency, replayability, back-pressure handling, and safe rollback, supported by automated tests, dashboards, and incident runbooks.

How do you lead multiple engineering teams while remaining technically credible without becoming a coding bottleneck?

I stay close to architecture decisions, operational metrics, customer problems, and technical reviews while delegating implementation ownership to strong engineering leaders. My role is to set direction, clarify trade-offs, remove cross-team blockers, develop people, and ensure teams have the standards and resources to make sound technical decisions independently.

How would you communicate a relevance-versus-latency trade-off to executive stakeholders?

I would frame the decision in terms of user outcomes, operational risk, and business impact rather than model details alone. I would present concise options with measurable expected gains, cost and timeline implications, and a recommended phased experiment so leadership can make an informed decision with clear success criteria.

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](mailto:hrgroup@netdocuments.co) 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

We are seeking a Senior Manager, Engineering to 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. Your team owns the embedding models and
indexing pipelines that power semantic search, and partners closely with product and vertical
teams across NetDocuments to evolve those capabilities for different use cases and industries.

This is a broad AI search mandate. Your team will not work on a single product in isolation but
will serve as the core platform layer enabling semantic experiences across the NetDocuments
ecosystem. You will drive the engineering vision, mentor engineering leaders, and create an
environment where innovation and operational rigor go hand in hand.

This position reports to the Director of Engineering, AI and will partner closely with peers across
Product, Architecture, and Data Science to ensure cohesive delivery of enterprise grade AI
powered search capabilities.

Drive Strategy & Execution

* 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.
Lead & Develop High Performing Teams
* 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.

Cross Functional Collaboration & Stakeholder Management

* 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.

Technical Leadership & Oversight

* 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.
Culture & Innovation
* 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.

What You’ll Need to Be Successful

* Bachelor’s degree in Computer Science, Engineering, or related field (advanced degree
preferred).
* 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

What Will Make You Stand Out

* 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.

What You’ll Love About NetDocuments

* The People!
* 90% healthcare premiums company covered
* HSA company contribution
* 401K 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

Compensation Transparency

The compensation range for this position is: $190,000 – $215,000

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.

Show more

[Apply now >](https://jobicy.com/jobs/156593-senior-manager-software-engineering-ai.md)

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