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Vector Databases Jobs in Springville, UT (NOW HIRING)

LVT

Senior Data Engineer

American Fork, UT · On-site

$94K - $128K/yr

Contribute to AI data infrastructure-support RAG pipelines, vector storage, and Snowflake Cortex integrations as one component of the broader engineering scope. * Mentor junior engineers and build ...

Proofpoint

Staff Software Engineer

Draper, UT

AI systems using structured LLM outputs, evals, token budgets, embeddings/vector search, vLLM/local ... Deep experience with relational databases, especially Postgres, schema design, query performance ...

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Vector Databases information

What are vector databases?

Vector databases are specialized databases designed to store, manage, and search high-dimensional vector data, which is commonly generated from machine learning models, such as embeddings from natural language processing or image recognition. They enable efficient similarity search operations, such as finding the most similar items to a given query vector, which is essential for applications like recommendation systems, semantic search, and AI-powered search engines. Unlike traditional databases that handle structured or unstructured data, vector databases are optimized for fast and scalable similarity searches on large datasets of vectors.

What are some common challenges faced when working with vector databases, and how can they be addressed?

Professionals working with vector databases often encounter challenges such as efficiently scaling to handle large datasets, ensuring low-latency similarity searches, and integrating the database with machine learning pipelines. To address these, teams typically implement distributed architectures, fine-tune indexing strategies, and collaborate closely with data engineers and machine learning specialists. Staying updated with the latest developments in vector database technologies and maintaining clear communication with cross-functional teams are also key to overcoming these challenges.

What is the difference between Vector Databases vs Data Engineers?

AspectVector DatabasesData Engineers
Required SkillsDatabase management, data modeling, query optimizationData pipeline development, ETL processes, programming
Work EnvironmentData storage systems, AI/ML projects, cloud platformsData infrastructure, cloud environments, big data tools
Industry UsageAI, machine learning, recommendation systemsData integration, analytics, data architecture

While Vector Databases focus on storing and querying high-dimensional vector data for AI applications, Data Engineers build and maintain data pipelines and infrastructure to support data analysis and machine learning workflows. Both roles are essential in data-driven industries but serve different functions within the data ecosystem.

What are the key skills and qualifications needed to thrive as a Vector Database Engineer, and why are they important?

Success as a Vector Database Engineer requires a strong background in computer science, database management, and experience with machine learning or AI-driven data systems. Familiarity with vector database platforms (such as Pinecone, Milvus, or Weaviate), cloud infrastructure, and proficiency in languages like Python are typically expected. Strong problem-solving skills, effective communication, and the ability to work cross-functionally help engineers stand out. These competencies are vital to efficiently design, deploy, and maintain scalable vector search solutions that power modern AI applications.
What cities near Springville, UT are hiring for Vector Databases jobs? Cities near Springville, UT with the most Vector Databases job openings:
Vector Databases jobs near you
Infographic showing various Vector Databases job openings in Springville, UT as of June 2026, with employment types broken down into 64% Full Time, 24% Part Time, and 12% Contract. Highlights an 72% Physical, 3% Hybrid, and 25% Remote job distribution.

Senior Data Engineer

LVT

American Fork, UT • On-site

$94K - $128K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago

Job description

ABOUT LVT
LVT is redefining how businesses operate in the physical world, moving beyond traditional security solutions to deliver AI-driven, actionable intelligence that makes sites smarter, safer, and more secure. Since pioneering our first mobile, solar-powered units, our commitment to scrappy, hands-on innovation has made us an established leader and one of the fastest-growing companies in intelligent site technology. We are building the next generation of solutions-from our physical units in the field to a powerful Agentic AI platform-that allows our customers to gain unprecedented visibility and control over safety, compliance, and operations. This is your chance to join a cutting-edge team that isn't just watching the world change, but actively building the technology that is changing it.
We're a team that's focused on growth and innovation, and we're proud that our crew, products, and leadership are being recognized for it.
  • A Top-Tier Growth Company: Named one of the Financial Times' Fastest Growing Companies 2025 and #10 on the Inc. 5000 Rocky Mountain Regional list for 2025.
  • Innovative Leadership: Our CEO, Ryan Porter, was named an EY Entrepreneur of the Year 2025, and our CTO, Steve Lindsey, was inducted into the Silicon Slopes CTO Hall of Fame in 2024.
  • Product & Software Excellence: We were named one of The Software Report's Top 100 Software Companies of 2023 and are a winner of the Security Today Govies Award for 2025.

ABOUT THIS ROLE
As Senior Data Engineer, you will own and evolve LVT's core data platform-architecting and operating the pipelines, transformations, and semantic models that power reporting, analytics, and business decisions at scale. This is a high-impact individual contributor role: your technical decisions will influence company-wide systems and competitive positioning, not just team-level outputs. You'll lead cross-functional data initiatives, set engineering standards, and contribute to the data infrastructure that supports LVT's growing AI capabilities.
This role is based in-office out of our Headquarters in American Fork, Utah.
ROLE RESPONSIBILITIES
  • Design, build, and maintain scalable, production-grade ELT pipelines that move data reliably from diverse source systems into a clean, well-governed data platform.
  • Architect and own LVT's Snowflake environment-performance tuning, dynamic tables, clustering strategies, storage optimization, and cost governance.
  • Develop and enforce semantic models that expose consistent, trusted business definitions across all reporting and analytics surfaces.
  • Define and drive data engineering standards that improve quality, reliability, and productivity across teams-not just within BI.
  • Lead cross-functional data initiatives, partnering with engineering, finance, operations, and product to deliver solutions that drive meaningful organizational outcomes.
  • Establish data quality infrastructure-implement validation, monitoring, and alerting frameworks that surface problems before they reach stakeholders.
  • Contribute to AI data infrastructure-support RAG pipelines, vector storage, and Snowflake Cortex integrations as one component of the broader engineering scope.
  • Mentor junior engineers and build strong partnerships with executives and business stakeholders to drive adoption of data solutions.
OUR IDEAL CANDIDATE
  • Seasoned Data Engineer: 7+ years building and operating production data pipelines using SQL, Python, and modern ELT tooling (dbt, Fivetran, Airflow, or equivalents). You've owned systems under pressure and know how to build for long-term reliability.
  • Snowflake Depth: Expert-level Snowflake experience-performance optimization, dynamic tables, data security, and Cortex familiarity. You know when and why to use each capability.
  • Semantic Modeling Ownership: Proven ability to design and maintain semantic or metrics layers that enforce consistent business logic across a complex, multi-team organization.
  • High-Impact Execution: You operate at the level of organizational strategy-your work influences competitive positioning, not just sprint delivery. You define standards, evaluate trade-offs, and build for the long term.
  • Data Quality Obsession: Reliability is non-negotiable. You instrument pipelines with observability, validation, and alerting from day one, and you define the standards others follow.
  • Leadership & Ownership: You own work from scoping through production and beyond. You influence company-wide technology decisions and mentor others along the way-without waiting to be told what to do.
  • AI Infrastructure Fluency: Familiar with AI/ML data patterns-RAG architectures, vector stores, embedding pipelines-and able to build the data infrastructure those systems require.
  • Executive Communication: You build partnerships with executives and cross-functional stakeholders, translating complex technical trade-offs into clear recommendations that earn trust and drive adoption.

BENEFITS
We believe you do your best work when your whole life is supported. We invest in our crew's health, families, and financial futures with a benefits package designed to support you inside and outside the office. Full-time benefits include, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits (401k match up to 4%), and flexible PTO.
LVT IS PROUD TO BE AN EQUAL OPPORTUNITY EMPLOYER. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. All candidates must pass a drug screening and background check upon employment. Some roles may also require passing a federal background check and fingerprinting. Must be authorized to work in the U.S. If reasonable accommodation is needed to participate in the job application or interview process, and/or to perform essential job functions, please reach out to your recruiter.

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