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Vector Databases Jobs in Nebraska (NOW HIRING)

Lead Cybersecurity - Insider Risk Engineer

Kimball, NE · On-site

$102K - $134K/yr

RAG (embeddings, vector databases, chunking strategies) * Prompt engineering and prompt versioning * Tool/function calling and agentic workflows * Output evaluation and red-teaming basics (prompt ...

Familiarity with large language model ecosystems and tools including prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG) pipelines * Experience fine-tuning and ...

Principal Software Engineer

Oak, NE · On-site

$134K - $180K/yr

Lead technical exploration of new tools - from vector databases and RAG frameworks to real-time video personalization - to keep VuMedi on the edge of applied AI. This role is ideal for someone who ...

Senior Software Engineer

Oak, NE · On-site

$122K - $161K/yr

Lead technical exploration of new tools - from vector databases and RAG frameworks to real-time video personalization - to keep VuMedi on the edge of applied AI. This role is ideal for someone who ...

... 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 Experience:

Forward Deployed AI Engineer

Omaha, NE · On-site +1

$200K - $250K/yr

Experience with modern AI tooling such as OpenAI, Anthropic, LangGraph, MCP, vector databases, or similar technologies. * Prior experience at a B2B SaaS company is highly preferred. * Strong Python ...

CyberSecurity AI Engineer

Lincoln, NE · On-site

$115K - $155K/yr

... vector databases, and training pipelines. • Build automated tools to detect and mitigate AI-related risks, such as anomalous model outputs and prompt injection attempts. • Conduct security ...

Working knowledge of RAG architectures, vector databases, embedding models, and the evaluation methodology * Experience building and publishing MCP servers, or building agents that consume them

... 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 ...

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Showing results 1-20

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 are popular job titles related to Vector Databases jobs in Nebraska? For Vector Databases jobs in Nebraska, the most frequently searched job titles are:
What cities in Nebraska are hiring for Vector Databases jobs? Cities in Nebraska with the most Vector Databases job openings:
Infographic showing various Vector Databases job openings in Nebraska as of June 2026, with employment types broken down into 60% Full Time, 35% Part Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 69% Physical, 2% Hybrid, and 29% Remote job distribution.
Lead Cybersecurity - Insider Risk Engineer

Lead Cybersecurity - Insider Risk Engineer

AT&T

Kimball, NE • On-site

$102K - $134K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


AT&T rating

7.3

Company rating: 7.3 out of 10

Based on 724 frontline employees who took The Breakroom Quiz

44th of 82 rated telecommunications companies


Job description

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.

Join AT&T and help shape the future of communications and technology that connect the world. We value innovators who seek to explore the unknown and challenge the status quo. Bring your bold ideas and fearless spirit to redefine connectivity and transform how people share stories and experiences. At AT&T, you won't just imagine the future-you'll build it.

The Insider Risk AI Engineer supports the design, development, and deployment of AI-enabled solutions that improve security operations and business workflows. This role focuses on building and iterating AI/ML and GenAI components (data prep, prompt/workflow design, evaluation, and lightweight model development), partnering with senior engineers, product owners, and operational teams to move prototypes into reliable services.

Key Responsibilities (AI-Focused)

  • Build AI prototypes and small services that solve defined problems (e.g., text classification, summarization, routing, search, Q&A, extraction).
  • Develop andmaintaindata pipelines for AI use cases (collect, clean, label, transform) using approved data sources.
  • Create and iterate on LLM prompts, agent/workflow logic, and retrieval-augmented generation (RAG) patterns for internal knowledge use cases.
  • Implement evaluation methods for AI outputs (quality,groundedness, hallucination checks, latency, cost) and report results.
  • Support model lifecycle tasks: experiment tracking, versioning, basicMLOps(packaging, deployment, monitoring).
  • Assistin integrating AI components into existing applications via APIs and lightweight UI or automation.
  • Document solutions (design notes, datasets, prompt versions, test cases) and contribute to internal reusable components.
  • Collaborate with stakeholders to define success metrics, acceptance criteria, and guardrails for AI-enabled features.

Example Use Cases (Optional)

  • Summarize tickets/incidents into standardized notes and action items.
  • Auto-tag and route requests based on description content.
  • Extract entities and indicators from unstructured text (emails, logs, reports).
  • Build an internal knowledge assistant over approved documentation with citations.
  • Generate draft playbooks/runbooks from templates and curated inputs.

Required Skills / Qualifications

  • 0-2 years of experience in software engineering, data engineering, analytics, or applied ML (internships/academic projects welcome).
  • Strong fundamentals in Python.
  • Working knowledge of:
  • Data structures, APIs, and basic software engineering practices (testing, code reviews, Git)
  • Data handling with pandas/SQL
  • ML basics (train/test splits, overfitting, common metrics) and/or LLM application patterns
  • Familiarity with at least one AI/ML framework or platform (coursework/labs acceptable):PyTorch, TensorFlow, scikit-learn, or common LLM tooling.
  • Ability to write clear documentation and communicate tradeoffs (quality vs cost vs latency).

Preferred Qualifications

  • Experience with GenAI application development patterns:
  • RAG (embeddings, vector databases, chunking strategies)
  • Prompt engineering and prompt versioning
  • Tool/function calling and agentic workflows
  • Output evaluation and red-teaming basics (prompt injection awareness, safety filters)
  • Exposure toMLOpsconcepts: CI/CD for ML, model registry, feature stores,monitoringdrift.
  • Experience with cloud services (any of AWS/Azure/GCP) and containerization (Docker).
  • Basic understanding of privacy/security fundamentals for AI systems (data handling, access controls, logging).

Preferred Qualifications (expanded to include cybersecurity-aligned experience)

  • Experience with GenAI application development patterns:
  • RAG (embeddings, vector databases, chunking strategies)
  • Prompt engineering and prompt versioning
  • Tool/function calling and agentic workflows
  • Output evaluation and red-teaming basics (prompt injection awareness, safety filters)
  • Exposure toMLOpsconcepts: CI/CD for ML, model registry, feature stores,monitoringdrift
  • Experience with cloud services (AWS/Azure/GCP) and containerization (Docker/Kubernetes)
  • Basic understanding of privacy/security fundamentals for AI systems (data handling, access controls, logging)

Cybersecurity-aligned preferred experience (nice-to-have):

  • Experience partnering with or supporting aSOC(e.g., translating analyst workflows into automations, alert triage enrichment, case summarization).
  • Familiarity withSIEM/EDR concepts and data(e.g., Splunk/Sentinel-like searches, endpoint telemetry, detection event schemas) to build AI features on top of security telemetry.
  • Exposure tothreat intelligence & IOC handling(IPs/domains/URLs/hashes) and using AI to extract/normalize indicators from unstructured text.
  • Working knowledge ofincident response lifecycleand case management processes (ticketing, evidence handling, basic post-incident reporting).
  • Awareness ofsecure software practices(secretsmanagement, least privilege, dependency hygiene) when building and deploying AI services.

Education/Experience: Bachelor's degree (BS/BA) desired in Computer Science or Cybersecurity. 5+ years of related experience. Certification is required in some areas.

Supervisor:

No

Our Lead Cybersecurity earns between$141,300-$211,900 USD Annual, not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.

Joining our team comes with amazing perks and benefits:

  • Medical/Dental/Vision coverage

  • 401(k) plan

  • Tuition reimbursement program

  • Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)

  • Paid Parental Leave

  • Paid Caregiver Leave

  • Additional sick leave beyond what state and local law require may be available but is unprotected

  • Adoption Reimbursement

  • Disability Benefits (short term and long term)

  • Life and Accidental Death Insurance

  • Supplemental benefit programs: critical illness/accident hospital indemnity/group legal

  • Employee Assistance Programs (EAP)

  • Extensive employee wellness programs

  • Employee discounts up to 50% off on eligible AT&T mobility plans and accessories,

  • AT&T internet (and fiber where available) and AT&T phone.

#LI-Onsite - Full-time office role-

Ready to join our team? Apply today.

Our Lead Cybersecurity jobs earn between $141,300.00 - $211,900.00 USD Annual. Not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.

Joining our team comes with amazing perks and benefits:

  • Medical/Dental/Vision coverage
  • 401(k) plan
  • Tuition reimbursement program
  • Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
  • Paid Parental Leave
  • Paid Caregiver Leave
  • Additional sick leave beyond what state and local law require may be available but is unprotected
  • Adoption Reimbursement
  • Disability Benefits (short term and long term)
  • Life and Accidental Death Insurance
  • Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
  • Employee Assistance Programs (EAP)
  • Extensive employee wellness programs
  • Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone

Weekly Hours:

40

Time Type:

Regular

Location:

USA:NC:Charlotte / Ibm Dr - Adm:8505 Ibm Dr

Salary Range:

$141,300.00 - $211,900.00

It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities.AT&T is a fair chance employer and does not initiate a background check until an offer is made.


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