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Vector Databases Jobs in Memphis, TN (NOW HIRING)

Evaluate and integrate LLMs, embedding models, and vector databases to support efficient and accurate retrieval and generation. Design and implement scaffolding and orchestration around LLMs ...

Junior AI Developer

Memphis, TN · On-site +1

$60K - $78K/yr

Evaluate and integrate LLMs, embedding models, and vector databases to support efficient and accurate retrieval and generation. Design and implement scaffolding and orchestration around LLMs ...

Technical Program Manager

Memphis, TN · On-site

$125K - $162K/yr

... vector databases, and LLM-based retrieval systems is highly desirable About Us Since opening our first store in 1979, AutoZone has grown into a leading retailer and distributor of automotive parts ...

Systems Engineer - Cloud Ops

Memphis, TN · On-site

$54.25 - $72.50/hr

Build and maintain infrastructure for Retrieval-Augmented Generation (RAG) pipelines and vector databases * Configure GPU-enabled node pools and optimize resource allocation for AI/ML workloads

Technical Program Manager

Memphis, TN

$125K - $162K/yr

... vector databases, and LLM-based retrieval systems is highly desirable Program Leadership Lead end-to-end execution of search platform initiatives from concept through production Drive alignment ...

Qualifications Required: * 2+ years of analytics consulting or industry experience * 2+ years of experience with artificial intelligence development tools, including vector databases such as Pinecone ...

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.
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.Net Developer (Local to Memphis Only)

Nineteen Eleven Solutions

Memphis, TN • On-site

Other

This job post has expired today. Applications are no longer accepted.


Job description

Job Title: .Net/React Developer 

Location: Memphis, TN candidates only

Duration: 12+ Months Contract 

Note: Must be living in Memphis in order to be considered.

Target candidates should bring 10+ years of progressive software engineering experience with expertise in full stack web application development, cloud-native architecture, and technical leadership. Successful candidates will have hands-on experience building scalable enterprise solutions using React, TypeScript, .NET Core, Azure, and modern API frameworks. Candidates should demonstrate success leading development teams, improving application performance, establishing development standards, implementing CI/CD practices, and delivering mission-critical enterprise solutions.

Core Technical Skills

Front-End: React, JavaScript, TypeScript, Redux, NextJS, Angular, AngularJS, Vue.js,

HTML5, CSS3, Tailwind, Bootstrap, Fluent UI, Sass

Back-End: .NET Core, C#, Node.js, Express.js, REST APIs, GraphQL, Web API, Python

Authentication & Security: OAuth 2.0, OpenID Connect, SSO, JWT

Cloud & DevOps: Microsoft Azure, Azure DevOps, CI/CD Pipelines, Git, Automated

Deployments

Data Technologies: SQL, MongoDB, Entity Framework, LINQ, Vector Databases

Testing: Cypress, Automated Testing, Unit Testing, Karma, Jasmine

Desired Career Progression / Relevant Experience

  • Led front-end teams, created reusable React functionality, implemented authentication solutions.
  • Developed enterprise applications using React, TypeScript, Redux, .NET Core, APIs, and automated testing.
  • Directed cloud-first initiatives, established architecture standards, selected technology stacks, and managed CI/CD implementation.
  • Architected complex business solutions, drove modernization efforts, and partnered with stakeholders on strategic initiatives.
  • Led AngularJS development and evaluated emerging technologies including Node.js and MongoDB.

Possible Certifications

Microsoft Azure Fundamentals (AZ-900) and other Microsoft cloud certifications.