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Vector Databases Jobs in Pleasant Grove, UT (NOW HIRING)

... with vector databases for domain-specific Q&A. Experience with Azure AI Foundry and Azure AI capabilities like document intelligence, computer vision, speech, and more. * Financial Services ...

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 ...

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 ...

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 ...

Google AI Lead Architect

Salt Lake City, UT · On-site

$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 ...

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 ...

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 ...

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 ...

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 ...

Showing results 41-60

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 are popular job titles related to Vector Databases jobs in Pleasant Grove, UT? For Vector Databases jobs in Pleasant Grove, UT, the most frequently searched job titles are:
What cities near Pleasant Grove, UT are hiring for Vector Databases jobs? Cities near Pleasant Grove, UT with the most Vector Databases job openings:
Infographic showing various Vector Databases job openings in Pleasant Grove, UT as of August 2026, with employment types broken down into 82% Full Time, 11% Part Time, 1% Temporary, and 6% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.

Manager - GenAI Full Stack Developer

Deloitte

Salt Lake City, UT • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

Deloitte professionals help organizations navigate business risks and opportunities across financial, operational, information technology (IT), and regulatory areas. In this Manager role, you will lead teams delivering end-to-end (full stack) Generative AI (GenAI) solutions-including Retrieval-Augmented Generation (RAG) and agentic AI-from strategy and architecture through build, deployment, and adoption.

Recruiting for this role ends on July 31st, 2026


Work you'll do

  • Lead client discovery, requirements, and solution shaping; translate needs into architecture, technical specifications, delivery plans, and acceptance criteria.
  • Design, build, and implement custom AI/GenAI solutions tailored to business workflows and risk considerations.
  • Architect and optimize agentic AI systems (e.g., tool-using agents, multi-step orchestration, multi-agent patterns) and integrate with enterprise platforms.
  • Lead end-to-end RAG implementations including ingestion, preprocessing, chunking, embeddings, indexing, retrieval, orchestration, and evaluation.
  • Drive GenAI model build activities (training, fine-tuning, validation), benchmarking, and continuous improvement of quality, safety, latency, and cost.
  • Oversee model deployment and production operations (monitoring, observability, incident response, iteration).
  • Lead development pods (planning, quality, delivery), including code/design reviews, mentoring, and engineering best practices.
  • Collaborate with cross-functional stakeholders (product, data, security, risk/compliance) to deliver scalable, maintainable solutions.
  • Evaluate emerging GenAI/agent frameworks and cloud services; prototype and recommend fit-for-purpose approaches.

The team
Our team culture is collaborative and encourages team members to take initiative and seek on-the-job learning opportunities. Audit & Assurance services are focused on engagements related to independent External Audit services, Accounting, Controls & Reporting Advisory, and Specialized Assurance & Sustainability. We bring together the diverse skills and industry experience of our people, leading-edge technology, and a global network to deliver high-quality audits of financial statements and internal controls over financial reporting, along with assurance reports and valuable advice and insights across the corporate reporting landscape. Learn more about Deloitte Audit & Assurance.

Qualifications
Required:

  • Bachelor's degree (or equivalent) in Computer Science, Engineering, Data Science, or a related field.
  • 6+ years of relevant experience in software engineering/full stack development and delivering AI/ML or GenAI-enabled solutions.
  • Experience leading teams and delivering client-facing solutions with clear ownership for quality and timelines.
  • Required technical skills (must have):
    • GenAI / NLP / Agentic AI
    • Python programming
    • Natural Language Processing (NLP)
    • Agentic AI, including LangChain, LangGraph, and LlamaIndex
    • RAG (Retrieval-Augmented Generation)
    • Prompt engineering
    • Vector databases (design/usage/integration)
    • Model build + deployment
    • GenAI model build: training, fine-tuning, validation
    • Model deployment (serving patterns, monitoring, iteration)
    • Containers (e.g., Docker)
    • Data engineering + APIs
    • ETL (extract, transform, load) and data engineering (pipelines, quality, preprocessing)
    • FastAPI (or equivalent) to build backend services
    • API development and integration (RESTful services)
    • Full stack engineering
    • JavaScript/TypeScript
    • HTML/CSS plus SASS/LESS
    • UI/UX design principles
    • Front-end frameworks: React, Angular, or Vue
    • Cloud AI/ML services across Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP)
    • Vertex AI experience
  • You should reside within a commutable distance of your assigned office with the ability to commute daily, if required
  • You can expect to co-locate on average 3 times a week with variations based on types of work/projects and client locations
  • Ability to travel up to 50%, on average, based on the work you do and the clients/sectors you serve
  • Limited immigration sponsorship may be available.

Preferred:

  • Cloud certification (AWS, Azure, or GCP) and/or AI/ML certification.
  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
  • Familiarity with AI/GenAI ethics and governance frameworks and implementing controls in production.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $151,470 to $218,025.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Deloitte professionals help organizations navigate business risks and opportunities across financial, operational, information technology (IT), and regulatory areas. In this Manager role, you will lead teams delivering end-to-end (full stack) Generative AI (GenAI) solutions-including Retrieval-Augmented Generation (RAG) and agentic AI-from strategy and architecture through build, deployment, and adoption.

Recruiting for this role ends on July 31st, 2026


Work you'll do

  • Lead client discovery, requirements, and solution shaping; translate needs into architecture, technical specifications, delivery plans, and acceptance criteria.
  • Design, build, and implement custom AI/GenAI solutions tailored to business workflows and risk considerations.
  • Architect and optimize agentic AI systems (e.g., tool-using agents, multi-step orchestration, multi-agent patterns) and integrate with enterprise platforms.
  • Lead end-to-end RAG implementations including ingestion, preprocessing, chunking, embeddings, indexing, retrieval, orchestration, and evaluation.
  • Drive GenAI model build activities (training, fine-tuning, validation), benchmarking, and continuous improvement of quality, safety, latency, and cost.
  • Oversee model deployment and production operations (monitoring, observability, incident response, iteration).
  • Lead development pods (planning, quality, delivery), including code/design reviews, mentoring, and engineering best practices.
  • Collaborate with cross-functional stakeholders (product, data, security, risk/compliance) to deliver scalable, maintainable solutions.
  • Evaluate emerging GenAI/agent frameworks and cloud services; prototype and recommend fit-for-purpose approaches.

The team
Our team culture is collaborative and encourages team members to take initiative and seek on-the-job learning opportunities. Audit & Assurance services are focused on engagements related to independent External Audit services, Accounting, Controls & Reporting Advisory, and Specialized Assurance & Sustainability. We bring together the diverse skills and industry experience of our people, leading-edge technology, and a global network to deliver high-quality audits of financial statements and internal controls over financial reporting, along with assurance reports and valuable advice and insights across the corporate reporting landscape. Learn more about Deloitte Audit & Assurance.

Qualifications
Required:

  • Bachelor's degree (or equivalent) in Computer Science, Engineering, Data Science, or a related field.
  • 6+ years of relevant experience in software engineering/full stack development and delivering AI/ML or GenAI-enabled solutions.
  • Experience leading teams and delivering client-facing solutions with clear ownership for quality and timelines.
  • Required technical skills (must have):
    • GenAI / NLP / Agentic AI
    • Python programming
    • Natural Language Processing (NLP)
    • Agentic AI, including LangChain, LangGraph, and LlamaIndex
    • RAG (Retrieval-Augmented Generation)
    • Prompt engineering
    • Vector databases (design/usage/integration)
    • Model build + deployment
    • GenAI model build: training, fine-tuning, validation
    • Model deployment (serving patterns, monitoring, iteration)
    • Containers (e.g., Docker)
    • Data engineering + APIs
    • ETL (extract, transform, load) and data engineering (pipelines, quality, preprocessing)
    • FastAPI (or equivalent) to build backend services
    • API development and integration (RESTful services)
    • Full stack engineering
    • JavaScript/TypeScript
    • HTML/CSS plus SASS/LESS
    • UI/UX design principles
    • Front-end frameworks: React, Angular, or Vue
    • Cloud AI/ML services across Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP)
    • Vertex AI experience
  • You should reside within a commutable distance of your assigned office with the ability to commute daily, if required
  • You can expect to co-locate on average 3 times a week with variations based on types of work/projects and client locations
  • Ability to travel up to 50%, on average, based on the work you do and the clients/sectors you serve
  • Limited immigration sponsorship may be available.

Preferred:

  • Cloud certification (AWS, Azure, or GCP) and/or AI/ML certification.
  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
  • Familiarity with AI/GenAI ethics and governance frameworks and implementing controls in production.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $151,470 to $218,025.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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