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Vector Databases Jobs in Springville, UT (NOW HIRING)

Sameday

Senior Backend Engineer

Lehi, UT · On-site

Experience with MongoDB and vector databases is a plus. • Experience in building and consuming RESTful APIs (FastAPI, OpenAPI to Typescript frontend) and implementing security best practices. • ...

Crew Career Center

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...

Patientco

Senior ML Engineer

Lehi, UT

$98K - $134K/yr

Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...

Waystar

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...

LVT

Senior AI Specialist

American Fork, UT

You have substantive, hands-on experience building and deploying LLM-based solutions - RAG pipelines, vector databases, agent frameworks, prompt engineering at scale. Using Copilot or ChatGPT at work ...

Epicor

Manager of Product Development | AI Platform

Lehi, UT · Hybrid

$107K - $134K/yr

Knowledge of modern artificial intelligence frameworks including retrieval-augmented generation, vector databases, orchestration frameworks, and observability tools * Familiarity with emerging ...

Amh

Product Engineering Architect

Draper, UT

Experience developing RAG solutions, vector databases, memory systems, prompt engineering strategies, and model optimization techniques. * Knowledge of modern AI development tools, coding assistants ...

Ancestry

Machine Learning Engineer, Co-op

Lehi, UT · Remote

Nice to have: Familiarity with LLM fine-tuning, retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, OpenSearch), LLM optimization, VLLM library, HuggingFace library or ...

BambooHR

Sr. Data Engineer

Draper, UT · Hybrid

$107K - $128K/yr

Design and manage vector databases and embedding pipelines to support semantic search and Retrieval-Augmented Generation (RAG). * Build and optimize retrieval pipelines including hybrid search ...

LVT

Senior AI Specialist

American Fork, UT · On-site

You have substantive, hands-on experience building and deploying LLM-based solutions - RAG pipelines, vector databases, agent frameworks, prompt engineering at scale. Using Copilot or ChatGPT at work ...

LVT

Senior AI Specialist

American Fork, UT · On-site

You have substantive, hands-on experience building and deploying LLM-based solutions -- RAG pipelines, vector databases, agent frameworks, prompt engineering at scale. Using Copilot or ChatGPT at ...

LVT

Senior Data Engineer

American Fork, UT

$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 ...

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All JobsVector Databases JobsVector Databases Jobs in Springville, UT

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 August 2026, with employment types broken down into 87% Full Time, 5% Part Time, 1% Temporary, and 7% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.

Senior Backend Engineer

Sameday

Lehi, UT • On-site

Full-time

Re-posted 19 hours ago

Job description

Job Summary:
Sameday is a company focused on revolutionizing customer engagement for home service businesses through advanced AI technologies. They are seeking a visionary Senior Backend Engineer to lead the architecture and development of AI-driven scheduling agents, playing a crucial role in the design and optimization of scalable backend systems.
Responsibilities:
• Act as a lead for the backend development function, collaborating effectively with the CEO/founder to accelerate progress and innovation.
• Design and develop scalable backend systems to support our AI-driven scheduling agents, ensuring high performance, reliability, and scalability.
• Build robust data ingestion, preprocessing, and feature engineering pipelines to enable efficient training and inference of AI models.
• Create and optimize RESTful APIs for seamless integration with frontend systems and third-party services.
• Optimize backend systems for performance and scalability to handle large-scale data and ensure real-time responsiveness.
• Stay updated with the latest advancements in backend development, distributed systems, and AI to drive continuous improvement and maintain a competitive edge.
Qualifications:
Required:
• Minimum of 5 years (desired: 9+ years) of experience in backend software development with a strong proficiency in Python.
• Strong experience in building and optimizing distributed systems, integrations, microservices, and cloud-based architectures (AWS preferred).
• Strong understanding of database systems, SQL, and ORM architectures. Experience with MongoDB and vector databases is a plus.
• Experience in building and consuming RESTful APIs (FastAPI, OpenAPI to Typescript frontend) and implementing security best practices.
• Demonstrated ability to autonomously drive architecture from concept to implementation.
Company:
Sameday is a virtual sales programme designed to assist home service providers in remaining available by phone throughout the day. Founded in 2021, the company is headquartered in Lindon, USA, with a team of 11-50 employees. The company is currently Early Stage.

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