2

Remote Ai Data Engineer Jobs in Utah (NOW HIRING)

Senior Backend Engineer - AI Platform

Salt Lake City, UT · On-site +1

$118K - $156K/yr

This is a remote position; however, the candidate must reside within 30 miles of one of the ... Strong understanding of data structures and algorithms, object-oriented design, and problem-solving ...

Senior Backend Engineer - AI Platform

Salt Lake City, UT · On-site +1

$118K - $156K/yr

This is a remote position; however, the candidate must reside within 30 miles of one of the ... Strong understanding of data structures and algorithms, object-oriented design, and problem-solving ...

Showing results 41-60

Remote Ai Data Engineer information

What are some common challenges faced by remote AI data engineers, and how can they be addressed?

Remote AI Data Engineers often encounter challenges such as coordinating with cross-functional teams across different time zones, ensuring data security when accessing sensitive datasets remotely, and maintaining effective communication for project updates. To address these, it's important to establish clear protocols for data sharing, leverage collaboration tools (like Slack or Jira), and schedule regular check-ins to align with team goals. Adopting strong version control practices and automated testing can also help streamline workflows and minimize errors in a distributed environment.

What is the difference between Remote Ai Data Engineer vs Data Scientist?

AspectRemote Ai Data EngineerData Scientist
Required CredentialsBachelor's in CS, Data Engineering, or related; experience with cloud platformsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentData pipelines, cloud infrastructure, codingData analysis, statistical modeling, visualization
Employer & Industry UsageTech companies, AI firms, startupsResearch institutions, tech companies, finance
Common Search & ComparisonYesYes

Remote Ai Data Engineers focus on building and maintaining data pipelines and infrastructure for AI applications, requiring skills in data engineering and cloud platforms. Data Scientists analyze data, develop models, and generate insights. While both roles work with data, Data Engineers prepare the data environment, whereas Data Scientists interpret and model the data. They often collaborate but serve different functions in AI and data projects.

What is a remote AI data engineer?

A Remote AI Data Engineer is a professional who designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) projects, all while working from a remote location. They are responsible for collecting, cleaning, transforming, and storing large datasets, ensuring data quality and accessibility for AI applications. These engineers collaborate with data scientists, software engineers, and stakeholders to deliver data solutions that power intelligent systems, often leveraging cloud technologies and distributed computing. Their work enables organizations to harness data for predictive analytics, automation, and decision-making—without being tied to a physical office.

What are the key skills and qualifications needed to thrive as a remote AI data engineer?

To thrive as a Remote AI Data Engineer, you need strong programming skills (Python, SQL), a solid understanding of data structures, machine learning principles, and typically a degree in computer science or related fields. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (AWS, GCP, or Azure), and experience with AI/ML frameworks like TensorFlow or PyTorch are commonly required. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote setting. These skills and qualities ensure robust AI data pipelines, effective model deployment, and seamless teamwork across distributed environments.

What are the most commonly searched types of Ai Data Engineer jobs in Utah?

The most popular types of Ai Data Engineer jobs in Utah are:

What job categories do people searching Remote Ai Data Engineer jobs in Utah look for?

The top searched job categories for Remote Ai Data Engineer jobs in Utah are:

What cities in Utah are hiring for Remote Ai Data Engineer jobs?

Cities in Utah with the most Remote Ai Data Engineer job openings:

Infographic showing various Remote Ai Data Engineer job openings in Utah as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Innovations and AI Solutions Engineer

Wsgr

Salt Lake City, UT • On-site, Remote

Full-time

Re-posted 24 days ago


Job description

Wilson Sonsini is the premier legal advisor to technology, life sciences, and other growth enterprises worldwide. We represent companies at every stage of development, from entrepreneurial start-ups to multibillion-dollar global corporations, as well as the venture firms, private equity firms, and investment banks that finance and advise them. The firm has approximately 1,100 attorneys in 17 offices: 13 in the U.S., two in China, and two in Europe. Our broad spectrum of practices and entrepreneurial spirit allow exceptional opportunities for professional achievement and career growth.

The Innovation and AI Solutions Engineer position is part of the firm's Innovation Department.This position will be responsible for developing, optimizing and growing the firm's corpus of innovation and AI solutions for both practice and enterprise side use cases, as well as optimizing data collection and flows across these solutions.The role will support our attorneys and staff with software development, low/no-code solutions, and data initiatives. The Innovation and AI Solutions Engineer is a self-directed, people-oriented employee who is comfortable supporting the development and data needs of the organization, including clients, attorneys, practice groups and administrative teams.

This position is available as a hybrid or remote work schedule.

Essential Duties, Responsibilities

  • Support innovation projects by facilitating and participating in discussions, meetings with management and department groups, developing business processes, implementing data integrations and recommending best practices on the effective use of data and data analytics tools.

  • Build and maintain innovation and AI solutions alongside optimal data API and pipeline architectures.

  • Design, build and implement machine learning models, including the development of AI Models and prompts for various applications.

  • Collaborate with business users and technical teams to support and improve how data is collected, analyzed and reported throughout the organization.

  • Analyze users needs to determine business and data requirements, effectively applying technology to meet the firm's strategic objectives.

  • Assemble and manage large, complex data sets that meet business and technical requirements.

  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, and improving infrastructure within assigned projects and data systems.

  • Build system infrastructure and processes for the efficient extraction, transformation, loading and integration of data to and from a wide variety of data sources using SQL, Power BI and Azure technologies.

  • Develop and/or apply analytics tools that utilize data pipelines to provide actionable insights into customer acquisition, operational efficiency, billing analytics, case outcomes, and other key business and legal practice performance metrics.

  • Ensure firm and client data security across multiple office locations, data centers, vendors and applications.

  • Develop data visualization and reporting tools to effectively convey meaningful insights from complex and diverse data sets.

  • Leverage statistics and computational techniques in problem solving.

  • Be familiar with common NLP and machine learning techniques.

  • Research and use applicable models in creative problem solving.

  • Work with GitHub and software version control.

  • Demonstrate the ability to efficiently and smartly document code and end-to-end processes.

  • Implement models in a production environment via custom API's and enterprise solutions. such as Azure.

Experience, Knowledge and Abilities

  • Extensive experience and working knowledge with SQL and relational databases, including query authoring, database management, and creating/maintaining large data stores in SQL and cloud platforms such as Azure or AWS.

  • Experience building and optimizing API's and data pipelines, architectures and data sets.

  • Strong analytic skills related to working with structured and unstructured datasets.

  • Ability to learn new tools and coding languages where required.

  • Ability to organize tasks and priorities under minimal supervision.

  • Experience performing root cause analysis on internal and external data, data integrations and processes to solve specific business problems and identify opportunities for improvement.

  • Experience developing processes that support data transformation, integrations, data structures, metadata, dependency and workflow management.

  • A successful history of manipulating, processing and extracting value from large, disconnected datasets.

  • Experience collaborating with cross-functional teams and stakeholders in a dynamic environment.

  • Ability to handle sensitive and confidential information responsibly.

  • Experience with AI/ML data preparation including feature engineering, data preprocessing, and dataset versioning for machine learning workflows.

  • Knowledge of data bias detection and mitigation techniques to ensure AI models are fair and representative across different legal contexts.

  • Experience with vector databases and embeddings for semantic search and retrieval-augmented generation (RAG) applications.

Technological Proficiency

  • Expertise in applying the following technologies:

    • SQL Server, T-SQL, SSIS & SSRS, Stored Procedures

    • DataWarehousing experience - ETL & ELT

    • PowerBI, Data Analysis Expressions (DAX)

    • Excel / PowerQuery

    • Programming and scripting languages: Python, R, C++, Julia, Javascript, SQL

    • API integration and development tools and scripting

    • Extensive experience working with a variety of data file formats, such as JSON, XML, SQL

  • Additional skills that would be highly advantageous include:

    • PowerShell

    • Regular Expression (Regex)

    • VBA, MS Access & Excel

    • Documentation & Process Mapping

    • Dynamic visualization tools, such as Microsoft Power BI, Tableau, Domo, etc.

    • Experience developing and applying machine learning models using Python, R, SQL and Azure Machine Learning

    • Experience integrating legal industry, line-of-business applications, such as SharePoint, Aderant Financial System, Salesforce.com/CRM, NetDocs/DMS

    • Large Language Model Integration: Experience with OpenAI API, Azure OpenAI, Anthropic Claude, or similar

    • Embedding Models: Familiarity with sentence transformers, OpenAI embeddings, or domain-specific legal embeddings

  • Law firm experience a plus.

Requirements

  • 4+ years of experience in a Data Engineer/DataOps-DevOps role.

  • Bachelor's degree and/or graduate degree in Computer Science, Data Science, Data Analytics, Information Systems or equivalent discipline.

  • Experience with Microsoft SQL Server and related Microsoft data management and integration technologies.

  • Excellent verbal and written communication and interpersonal skills

Preferred

  • AI/ML Data Preparation Certification or equivalent coursework in machine learning data engineering.

  • Experience with legal technology platforms and understanding of legal workflow requirements.

  • Knowledge of data privacy regulations (GDPR, CCPA, HIPAA) as they apply to AI systems in legal contexts.

The primary location for this job posting is in Palo Alto, but other locations may be listed. The actual base pay offered will depend upon a variety of factors, including but not limited to the selected candidate's qualifications, years of relevant experience, level of education, professional certifications and licenses, and work location. The anticipated pay range for this position is as follows:Palo Alto, New York, San Francisco: $116,875 - $158,125 per year. Austin, Boston, Boulder, Century City, Delaware, Los Angeles, Salt Lake City, San Diego, Seattle, Washington, D.C., and all other locations: $105,400 - $142,600 per year.

The compensation for this position may include a discretionary year-end merit bonus based on performance. We offer a highly competitive salary and benefits package.

Benefits information can be found here. Equal Opportunity Employer (EOE).