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Ai Rag Jobs in Pasadena, TX (NOW HIRING)

Neshent Technologies

AI Architect

Deer Park, TX · Remote

$56.50 - $74.50/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

Pearland, TX · Remote

$56.25 - $74/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

Houston, TX · Remote

$60.25 - $79.25/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

Bellaire, TX · Remote

$56.75 - $74.75/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

Meadows Place, TX · Remote

$54.25 - $71.50/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

Houston, TX · Remote

$60.25 - $79.25/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

Galena Park, TX · Remote

$53.50 - $70.50/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

Pasadena, TX · Remote

$57.50 - $75.75/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

Highlands, TX · Remote

$55 - $72.50/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

La Porte, TX · Remote

$59.25 - $78/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Neshent Technologies

AI Architect

West University Place, TX · Remote

$58.25 - $77/hr

Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic ... for cloud and AI platforms. * Collaborate with business stakeholders, engineering teams, and ...

Fracht USA

AI INTEGRATION ENGINEER

Houston, TX · On-site

$89K - $121K/yr

POSITION OVERVIEW The AI Integration Engineer is responsible for designing, building, and ... Design and implement retrieval patterns (RAG) to ground agents in company and client data ...

Kirkland & Ellis LLP

AI Engineer II

Chicago, IL · On-site

$116K - $144K/yr

Build and deploy AI models, large language model (LLM)-powered applications, and retrieval-augmented generation (RAG) pipelines across enterprise environments. * Quality & Evaluation: Create and ...

Kirkland & Ellis LLP.

AI Engineer II

Houston, TX · On-site

$116K - $144K/yr

Build and deploy AI models, large language model (LLM)-powered applications, and retrieval-augmented generation (RAG) pipelines across enterprise environments. * Quality & Evaluation: Create and ...

Deloitte

Google AI Architect

Houston, TX

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Fervo Energy

Agentic AI Engineer

Houston, TX · On-site

Design and deploy end-to-end agentic AI workflows using planner-worker, orchestrator-executor, multi-agent, and RAG-based architectures * Build reusable components and reference patterns for tool ...

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Ai Rag information

See Pasadena, TX salary details

$29.2K

$53.2K

$76.3K

How much do ai rag jobs pay per year?

As of Aug 22, 2026, the average yearly pay for ai rag in Pasadena, TX is $53,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,800.00 and $59,400.00 per year, depending on experience, location, and employer.

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What cities near Pasadena, TX are hiring for Ai Rag jobs?

Cities near Pasadena, TX with the most Ai Rag job openings:

Ai Rag jobs near you

AI Architect

Neshent Technologies

Deer Park, TX • Remote

$56.50 - $74.50/hr

Full-time

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

Job description

We are seeking an experienced AI Architect to lead the design and delivery of enterprise-scale AI, cloud modernization, and digital transformation initiatives. The ideal candidate will have deep expertise in Azure and Google Cloud Platform (GCP), enterprise application architecture, cloud-native development, and Generative AI technologies. This role will drive AI strategy, architect scalable and secure solutions, modernize legacy applications, and lead the implementation of intelligent enterprise platforms.

Roles and Responsibilities
  • Lead enterprise application modernization, cloud transformation, and AI architecture initiatives.
  • Design scalable, secure, and highly available solutions across Microsoft Azure and Google Cloud Platform (GCP).
  • Define cloud architecture, modernization roadmaps, governance frameworks, and technology standards aligned with business objectives.
  • Modernize legacy applications using cloud-native architectures, microservices, APIs, containers, and Azure PaaS services.
  • Lead migration of enterprise applications from on-premises environments to Azure/GCP.
  • Architect and implement enterprise AI and Generative AI solutions using Azure AI and OpenAI technologies.
  • Develop enterprise copilots, intelligent assistants, document intelligence platforms, and knowledge management solutions.
  • Design Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and semantic search.
  • Establish security, scalability, performance, reliability, and operational best practices for cloud and AI platforms.
  • Collaborate with business stakeholders, engineering teams, and product leaders to deliver customer-facing digital solutions.
  • Mentor development teams and provide technical leadership throughout solution delivery.
Required Qualifications
  • 10+ years of software engineering and enterprise application delivery experience.
  • 5+ years of Azure and/or Google Cloud Platform (GCP) architecture experience.
  • 3+ years of hands-on experience delivering AI and Generative AI solutions.
  • Proven experience leading enterprise digital transformation and customer-facing platform initiatives.
  • Strong expertise in cloud architecture, application modernization, and enterprise solution design.
  • Experience designing microservices-based, API-driven, cloud-native applications.
  • Strong knowledge of architectural governance, cloud security, and operational best practices.
  • Excellent leadership, stakeholder management, and solution architecture skills.

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