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Remote Retrieval Augmented Generation Jobs in Orem, UT

RainFocus is looking for a Full Stack Developer to help us build the next generation of tools that ... Build and iterate on advanced prototypes that integrate LLMs, APIs, and retrieval pipelines

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RainFocus is looking for a Full Stack Developer to help us build the next generation of tools that ... Build and iterate on advanced prototypes that integrate LLMs, APIs, and retrieval pipelines

Remote Retrieval Augmented Generation information

What is remote retrieval augmented generation?

Remote Retrieval Augmented Generation (RAG) is an advanced AI technique that combines large language models with external information sources. In a remote RAG setup, the model retrieves relevant data from remote databases or APIs during the generation process, enhancing its responses with up-to-date or domain-specific knowledge. This approach is widely used in applications that require accurate, context-aware answers, such as chatbots, search engines, and virtual assistants. By leveraging remote retrieval, RAG systems can access a broader range of information without needing to store all data locally.

What skills and qualifications are needed to thrive as a remote retrieval augmented generation engineer?

To thrive as a Remote Retrieval Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and information retrieval, often backed by a degree in computer science or a related field. Familiarity with tools and frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and experience with retrieval systems such as Elasticsearch or FAISS are typically required. Problem-solving, effective communication, and adaptability are important soft skills for collaborating remotely and iterating on rapidly evolving AI solutions. These skills ensure the engineer can design, deploy, and optimize robust RAG systems that effectively combine retrieval and generation for high-quality AI outputs.

What are common challenges faced by professionals working in remote retrieval augmented generation roles, and how can they be addressed?

Professionals in Remote Retrieval Augmented Generation (RAG) roles often encounter challenges related to integrating diverse data sources, ensuring low latency in information retrieval, and maintaining the quality and relevance of augmented outputs. Coordinating effectively with distributed teams and adapting to rapidly evolving AI technologies are also common hurdles. To address these, staying current with best practices in data engineering, leveraging robust APIs, and participating in regular team check-ins can help ensure smooth collaboration and system performance.

What is the difference between Remote Retrieval Augmented Generation vs Remote Data Scientist?

AspectRemote Retrieval Augmented GenerationRemote Data Scientist
CredentialsAI/ML knowledge, programming skillsStatistics, programming, domain expertise
Work EnvironmentAI development, NLP projectsData analysis, model building
Industry UsageAI, NLP, machine learningTech, finance, healthcare
Search & ComparisonOften compared for AI roles involving language modelsCompared for data analysis roles

Remote Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, requiring expertise in AI, NLP, and programming. Remote Data Scientists analyze data, build models, and interpret results, often with statistical and domain knowledge. While both roles may work remotely and involve data handling, Retrieval Augmented Generation emphasizes AI model development, whereas Data Scientists focus on data analysis and insights.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Orem, UT?

The most popular types of Retrieval Augmented Generation jobs in Orem, UT are:

What are popular job titles related to Remote Retrieval Augmented Generation jobs in Orem, UT?

For Remote Retrieval Augmented Generation jobs in Orem, UT, the most frequently searched job titles are:

What job categories do people searching Remote Retrieval Augmented Generation jobs in Orem, UT look for?

The top searched job categories for Remote Retrieval Augmented Generation jobs in Orem, UT are:

What cities near Orem, UT are hiring for Remote Retrieval Augmented Generation jobs?

Cities near Orem, UT with the most Remote Retrieval Augmented Generation job openings:

Senior Manager, Software Engineering - AI

NetDocuments

Lehi, UT • On-site, Remote

Full-time

Medical, Life, Retirement, PTO

Re-posted 11 days ago


Job description

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.