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Vector Databases Jobs in Cleburne, TX (NOW HIRING)

INSPYR Solutions

Sr. Engineer

Fort Worth, TX · On-site

$100K - $137K/yr

Experience with event-driven architectures (Kafka, EventBridge), vector databases, observability tools (Datadog, Splunk, OpenTelemetry), agent evaluation frameworks, FastAPI/Flask, async Python ...

Pwc

ERP AI Engineer - Manager

Fort Worth, TX

$99K - $232K/yr

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

Pwc

CTIO AI Engineering Manager

Fort Worth, TX

$73K - $244K/yr

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

CAE, Inc.

Senior Visual Database Lead

Arlington, TX · On-site

$95K - $129K/yr

... and vector data * 8+ years' experience in Photoshop, primarily in image clean up, and color ... database creation for multiple image generation systems, such as Aechelon, MetaVR, Vital, or ...

Caeus

Senior Visual Database Lead

Arlington, TX

$95K - $129K/yr

... and vector data * 8+ years' experience in Photoshop, primarily in image clean up, and color ... database creation for multiple image generation systems, such as Aechelon, MetaVR, Vital, or ...

Deloitte

Google AI Lead Architect

Fort Worth, TX · On-site

$53 - $72.50/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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All JobsVector Databases JobsVector Databases Jobs in Cleburne, TX

Vector Databases information

What is the salary of a vector database developer?

The salary of a vector database developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and company size. Skilled developers with expertise in machine learning, data structures, and database management may earn higher salaries, especially in tech hubs or with advanced certifications.

Are vector databases the future?

Vector database jobs involve managing and optimizing databases designed for high-dimensional vector data, which are essential for AI and machine learning applications. As AI continues to grow, demand for professionals skilled in vector database technologies and related tools like embedding models is expected to increase, making this a promising field for future job opportunities.

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 can you do with a vector database?

A vector database is used in roles involving data management and machine learning to store, search, and retrieve high-dimensional vector representations of data such as images, text, or audio. It enables efficient similarity searches, supporting applications like recommendation systems, natural language processing, and computer vision. Working with a vector database often requires knowledge of data structures, indexing techniques, and programming skills in languages like Python or C++.

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 the top 5 vector databases?

Top vector databases used in data management and AI applications include Pinecone, Weaviate, FAISS, Milvus, and Annoy. These databases are optimized for storing and searching high-dimensional vector data, often requiring skills in machine learning and database management. They are widely adopted for tasks like similarity search and recommendation systems.
What cities near Cleburne, TX are hiring for Vector Databases jobs? Cities near Cleburne, TX with the most Vector Databases job openings:
Vector Databases jobs near you
Infographic showing various Vector Databases job openings in Cleburne, TX as of July 2026, with employment types broken down into 64% Full Time, and 36% Contract. Highlights an 92% In-person, and 8% Remote job distribution.
Software Engineer (AI/GenAI Platforms)

Software Engineer (AI/GenAI Platforms)

Allstate

Fort Worth, TX • On-site

Full-time

Posted 21 hours ago

Allstate Insurance rating

7.5

Company rating: 7.5 out of 10

Based on 557 frontline employees who took The Breakroom Quiz

198th of 277 rated insurance

Job description

At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers' evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.

Job Description

Our Mission
We are on a mission to unlock business value from petabyte-scale unstructured enterprise data by building cutting-edge AI, GenAI, and Agentic AI capabilities on top of our Unstructured Data Platform.
In this role, you'll help transform massive volumes of documents, voice recordings, images, and video into actionable intelligence, powerful insights, and autonomous AI systems that drive real business decisions.
You will design and build AI-driven systems that combine large-scale data engineering, machine learning, and generative AI to power nextgeneration enterprise capabilities.
What You'll BringCore Engineering Skills
  • Python (required) for AI/ML development
  • Java, with hands-on experience building backend services and enterprise integrations
  • Ability to work across both Python and Java codebases, integrating AI/ML components into Java-based enterprise systems
  • Proven experience building and operating production-grade AI/ML systems
  • Strong understanding of data pipelines and distributed data processing
AI / GenAI Expertise

Hands-on experience in one or more of the following areas:

  • Large Language Models (LLMs): Working with foundation models and fine-tuning
  • Retrieval Augmented Generation (RAG): Building context-aware AI applications
  • Vector Search & Embeddings: Semantic search and similarity matching
  • Multimodal AI: Processing text, voice, images, and video
  • AI Agents / Agent Frameworks: Building autonomous AI workflows
  • Prompt Engineering: LLM orchestration and optimization
  • Semantic Models: Building and leveraging semantic data models

Framework Experience

  • LangChain, LlamaIndex, Semantic Kernel
  • Hugging Face
  • OpenAI, AWS Bedrock, Azure OpenAI
Data & Platform Technologies

Experience working in large-scale enterprise data environments, including:

Architecture

  • Data lakes and lakehouse architectures

Analytics

  • Microsoft Fabric, Azure Fabric, or similar analytics platforms

Streaming

  • Kafka and event-driven architectures

Cloud Services

  • Amazon Web Services (AWS)

Datastores

  • MongoDB Atlas
  • Amazon DocumentDB
  • Vector databases (nice to have)
ML / AI Platforms
  • Amazon SageMaker or similar ML platforms
  • AWS Bedrock for foundation model access and deployment
  • Model training, evaluation, and deployment
  • Experience with MLOps workflows
Observability & Reliability
  • Monitoring and troubleshooting AI and data pipelines
  • Experience with observability tools such as Datadog and AWS CloudWatch
Why Join Us?
  • Work on petabyte-scale unstructured data challenges
  • Build with the latest GenAI and Agentic AI technologies
  • Transform unstructured data into enterprise intelligence
  • Join a team shaping the future of AI-powered decision making

#LI-JK1

Skills

Amazon SageMaker, Amazon Web Services (AWS), Apache Kafka, Communication, Continuous Integration Software, Data Analysis, Large Language Model (LLM) Fine-Tuning, Machine Learning (ML), Python (Programming Language), Semantics, Software Development, Vector Databases

Compensation

Compensation offered for this role is 85,000.00 - 145,075.00 annually and is based on experience and qualifications.

The candidate(s) offered this position will be required to submit to a background investigation.

Joining our team isn't just a job - it's an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger - a winning team making a meaningful impact.

Allstate generally does not sponsor individuals for employment-based visas for this position.

Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.

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It is the Company's policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee's ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.

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