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Vector Databases Jobs in Springdale, AR (NOW HIRING)

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

Senior IT Data Engineer (Onsite)

Springdale, AR · On-site

$93K - $127K/yr

Lead code reviews, design and deploy agentic AI architectures and multi-agent systems that automate data engineering workflows, including RAG systems, vector databases, and LLM-integrated platforms.

Principal, Data Scientist

Bentonville, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Rogers, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Goshen, AR · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Principal, Data Scientist

Noel, MO · On-site

$110K - $220K/yr

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

Hands-on experience developing GenAI solutions using Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), Skills, vector databases, and agentic workflows.

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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 job categories do people searching Vector Databases jobs in Springdale, AR look for? The top searched job categories for Vector Databases jobs in Springdale, AR are:
ERP AI Engineer - Manager

ERP AI Engineer - Manager

Pwc

Fayetteville, AR • On-site

$99K - $232K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 29 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 73 frontline employees who took The Breakroom Quiz

20th of 57 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Oracle

Management Level

Manager

Job Description & Summary

At PwC, our people in business application consulting specialise in consulting services for a variety of business applications, helping clients optimise operational efficiency. These individuals analyse client needs, implement software solutions, and provide training and support for seamless integration and utilisation of business applications, enabling clients to achieve their strategic objectives.
In Oracle data and analytics at PwC, you will utilise Oracle's suite of tools and technologies to work with data and derive insights from it. You will be responsible for tasks such as data collection, data cleansing, data transformation, data modelling, data visualisation, and data analysis using Oracle tools like Oracle Database, Oracle Analytics Cloud, Oracle Data Integrator, Oracle Data Visualization, and Oracle Machine Learning.
Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Analyse and identify the linkages and interactions between the component parts of an entire system.
Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
Develop skills outside your comfort zone, and encourage others to do the same.
Effectively mentor others.
Use the review of work as an opportunity to deepen the expertise of team members.
Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
The Opportunity
As part of the Data and Analytics Engineering team, you will serve as both a technical leader and a trusted advisor to clients, combining AI/ML knowledge with business acumen to design and deliver AI solutions that drive measurable client outcomes. As a Manager, you will lead teams of data scientists and ML engineers, manage client relationships, and translate complex business challenges into AI-driven strategies and solutions. This role offers the chance to shape AI solution architecture while driving innovation and excellence in client engagements.
Responsibilities
- Lead and mentor teams of data scientists and ML engineers
- Manage client relationships and promote satisfaction with deliverables
- Translate intricate business challenges into AI-driven strategies
- Design and implement AI solution architectures
- Drive innovation and excellence in client engagements
- Analyze data to derive actionable insights and solutions
- Collaborate with stakeholders to align on project objectives
- Uphold exceptional standards of quality and integrity in every task
What You Must Have
- Bachelor's Degree
- At least 7 years of experience in AI/ML engineering, data science, or a related technical role
What Sets You Apart
- Master's Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related field preferred
- Experience with Large Language Models and prompt engineering
- Building scalable, cloud-native microservices and containerized deployments
- Proficiency with MLOps tooling and CI/CD pipelines for ML
- Experience with vector databases and semantic search architectures
- Translating complex business problems into AI solution designs
- Contributing to business development and proposal writing
- Cloud certifications in AI/ML or solutions architecture preferred
- Familiarity with Responsible AI principles and bias mitigation practices

Travel Requirements

Up to 60%

Job Posting End Date

The salary range for this position is: $99,000 - $232,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

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