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Vector Databases Jobs in Ogden, UT (NOW HIRING)

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

Deployed RAG systems including embedding models, vector databases, hybrid search, and retrieval optimization * Designed LLM strategies covering tool calling, structured outputs, prompt engineering ...

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

Deployed RAG systems including embedding models, vector databases, hybrid search, and retrieval optimization * Designed LLM strategies covering tool calling, structured outputs, prompt engineering ...

... with vector databases and semantic search architectures - Translating complex business problems into AI solution designs - Contributing to business development and proposal writing - Cloud ...

... database systems. * Interface with HARM personnel to update the ARMS (or future Government-mandated ... Vector CSP, LLC is an Equal Opportunity Employer. We do not discriminate in employment decisions ...

... vector databases and orchestration tools like LangChain - Translating complex business problems into software-engineered AI solutions - Deploying on cloud platforms like AWS, GCP, Azure ...

LLM‑based application development, retrieval‑augmented generation architectures, agentic design patterns, prompt engineering, or vector databases. * Strong technical problem‑solving ability and ...

Posted today

Google AI Lead Architect

Salt Lake City, UT

$53.50 - $73.25/hr

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement ... databases. Should have experience in leveraging various GenAI tools to accelerate software ...

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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 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 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 popular job titles related to Vector Databases jobs in Ogden, UT?

For Vector Databases jobs in Ogden, UT, the most frequently searched job titles are:

What cities near Ogden, UT are hiring for Vector Databases jobs?

Cities near Ogden, UT with the most Vector Databases job openings:

Senior Java Developer[Business Automation & AI]-[lOCAL TO UTAH]

SmartIPlace

Salt Lake City, UT • On-site

$55.50 - $70.75/hr

Contractor

Re-posted 17 days ago


Job description

Position: Senior Java Developer (Business Automation & AI)

Location:  Salt Lake City, Utah, 84111

Interview mode: Onsite interviews

Visa: ANY

 

Interviews will be held onsite.

Hybrid role

Required Technical Skills:

  • Java Mastery: 3-5 years of professional experience with Java (8/11/17+), including Spring Boot or Quarkus.
  • Rule Engines: Hands-on experience writing and debugging Drools rules and implementing DMN (Decision Model and Notation).
  • Cloud Native Automation: Proven experience with Kogito for building cloud-native business processes.
  • AWS AI/ML Stack: Experience configuring AWS Bedrock (Knowledge Bases, Agents, or Prompt Engineering).
  • **Proficiency in managing Amazon S3 for large-scale document storage and metadata tagging.
  • Documentation Transformation: Experience (or strong scripting ability) in converting Adobe RoboHelp (HTML/XML) into structured formats (Markdown/JSON) for AI consumption.
  • Modern DevOps: Experience with Git, CI/CD pipelines, and containerization (Docker/Kubernetes).

 

Preferred Qualifications:

  • Experience with Vector Databases (Amazon OpenSearch, Pinecone, or Milvus).
  • Understanding of Python (specifically for BeautifulSoup/Pandoc-based document parsing).
  • Knowledge of BPMN 2.0 standards.
  • AWS Certified Developer or AWS Machine Learning Specialty certification.

Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

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