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Ai Rag Jobs in Forney, TX (NOW HIRING)

NTT DATA North America

AI Product Manager

Dallas, TX · On-site

... RAG pipelines, prompt engineering, and validation loops • Drive integrations with observability, incident management, and deployment systems • Conduct user research and translate production ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and ... Monitor, troubleshoot, and continuously improve AI model performance and system reliability

Saransh Inc

Conversational AI Developer

Irving, TX · On-site

Leverage LLMs and RAG: Utilize and fine-tune large language models (LLMs) and implement Retrieval-Augmented Generation (RAG) to enhance the accuracy and relevance of AI responses by incorporating ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and ... Monitor, troubleshoot, and continuously improve AI model performance and system reliability

Select Minds LLC

AI Testing Architect

Dallas, TX · On-site

$120K - $135K/yr

Build and deploy LLM-based workflows (e.g., test case generation, RAG-based validation, anomaly detection) * Evaluate, select, and integrate AI tools and frameworks for QA and SDLC use cases

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and ... Monitor, troubleshoot, and continuously improve AI model performance and system reliability

Confie

AI Engineer

Addison, TX · On-site +1

$110K - $140K/yr

Build advanced RAG systems with vector databases, hybrid search (dense + sparse retrieval), and reranking for domain-specific chatbots and knowledge retrieval. Develop generative AI solutions for ...

OMS MEDICAL BILLING LLC

AI/ML Engineer

Addison, TX · Hybrid

Contribute to our AI architecture and platform decisions: model gateways, vector stores, RAG patterns, agent frameworks What We're Looking For * 6+ years of Python engineering; 3+ years building ...

CYNET SYSTEMS

AI/ML Engineer

Plano, TX · On-site

$60/hr

Solid knowledge of Prompt engineering/context engineering, Long-term vs short-term memory, Token management, RAG & Vectorization, Cache management, different frameworks of Agentic AI, including. Nice ...

Wells Fargo

Senior Specialty AI Engineer

Irving, TX · Hybrid

$117K - $155K/yr

RAG Pipeline Development * Build and maintain ingestion pipelines: document parsing, chunking ... Vertex AI & Cloud Engineering * Develop and deploy services using Google Vertex AI (model endpoints ...

RealPage, Inc.

AI Engineer (DFW Area)

Richardson, TX · On-site

RAG & Knowledge Integration * Architect and implement RAG pipelines: * Choose and configure vector databases (e.g., PGVector, Vertex AI Search, Pinecone, etc.) * Build ingestion pipelines for ...

RealPage, Inc.

AI Engineer (DFW Area)

Richardson, TX · On-site

$107K - $182K/yr

RAG & Knowledge Integration * Architect and implement RAG pipelines: * Choose and configure vector databases (e.g., PGVector, Vertex AI Search, Pinecone, etc.) * Build ingestion pipelines for ...

RealPage, Inc.

Agentic AI Developer III

Richardson, TX · On-site

$129K - $220K/yr

RAG & Knowledge Integration * Architect and implement RAG pipelines: * Choose and configure vector databases (e.g., PGVector, Vertex AI Search, Pinecone, etc.) * Build ingestion pipelines for ...

RealPage, Inc.

AI Engineer III HYBRID

Richardson, TX · On-site

RAG & Knowledge Integration * Architect and implement RAG pipelines: * Choose and configure vector databases (e.g., PGVector, Vertex AI Search, Pinecone, etc.) * Build ingestion pipelines for ...

RealPage, Inc.

AI Engineer (DFW Area)

Richardson, TX · On-site

$107K - $182K/yr

RAG & Knowledge Integration * Architect and implement RAG pipelines: * Choose and configure vector databases (e.g., PGVector, Vertex AI Search, Pinecone, etc.) * Build ingestion pipelines for ...

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All JobsAi Rag JobsAi Rag Jobs in Forney, TX

Ai Rag information

See Forney, TX salary details

$28.8K

$52.5K

$75.2K

How much do ai rag jobs pay per year?

As of Jul 20, 2026, the average yearly pay for ai rag in Forney, TX is $52,471.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,100.00 and $58,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?

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 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.

Which AI is best at RAG?

For an AI Rag role, the best AI systems for Retrieval-Augmented Generation (RAG) tasks typically include models like OpenAI's GPT-4, Google's Bard, and Meta's Llama 2, which are capable of integrating retrieval components with language generation. Success in RAG depends on the model's ability to efficiently access and incorporate external data, as well as the implementation of effective retrieval mechanisms and fine-tuning. Skills in natural language processing, knowledge of retrieval systems, and experience with relevant tools are essential for this role.

What engineer makes 500,000 a year?

Senior software engineers, especially those working in high-demand fields like artificial intelligence or machine learning at large tech companies, can earn $500,000 or more annually. Compensation often includes base salary, bonuses, and stock options, and requires advanced skills, extensive experience, and often a master's or Ph.D. in a related field.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in data science, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong track record of innovation and leadership in the field.

What are AI RAGs?

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.

Which 3 jobs will survive AI?

AI Rag is a role that involves managing and interpreting AI outputs, and jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to survive AI automation. Examples include healthcare professionals, skilled tradespeople, and roles in education. These jobs often require human judgment, interpersonal skills, and adaptability that AI cannot fully replicate.

What are some common challenges faced by AI RAG (Retrieval-Augmented Generation) 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.
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Ai Rag jobs near you

AI Product Manager

NTT DATA North America

Dallas, TX • On-site

Full-time

Posted 20 days ago

Job description

Job Summary:
NTT DATA North America is a trusted global innovator of business and technology services. They are seeking an AI Product Manager to define the strategy, roadmap, and execution for Generative AI solutions, collaborating with various teams to deliver high-impact AI products.
Responsibilities:
• Define product vision, strategy, and roadmap for agentic AI systems
• Translate user pain points into product requirements, user stories, and success metrics
• Lead end-to-end lifecycle for LLM-based products from discovery to iteration
• Establish evaluation frameworks for LLMs and prioritize RAG pipelines, prompt engineering, and validation loops
• Drive integrations with observability, incident management, and deployment systems
• Conduct user research and translate production challenges into roadmap priorities
• Own AI safety, governance, reliability, and fallback strategies
• Define and monitor KPIs such as cost, latency, and user satisfaction
• Own data and knowledge strategy including RAG pipeline and data validation
• Lead product design reviews and promote data-driven experimentation
• Mentor teams on AI product management and best practices
Qualifications:
Required:
• Bachelor's degree in Engineering, Computer Science, or equivalent
• 10–15 years of experience with significant product management exposure
• 5 + yr Experience leading large-scale AI/ML or cloud-based product initiatives
• 5 + yrs Strong understanding of LLMs, agentic systems, RAG pipelines, and MLOps
• 5 + yrs Ability to engage deeply with engineering teams on technical topics
• Strong communication skills for technical and non-technical stakeholders
• Experience working in fast-paced, cross-functional environments
• Strong analytical and data-driven decision-making skills
• Proven ability to influence without direct authority
Preferred:
• Experience working with enterprise-scale production environments
• Familiarity with observability and incident management tools
• Experience in prompt engineering and LLM evaluation frameworks
• Exposure to AI safety, governance, and compliance standards
• Prior experience mentoring product managers or leading product communities
• Knowledge of cloud platforms such as AWS or Google Cloud in AI contexts
Company:
NTT DATA, Inc. is a trusted global innovator of business and technology services. Founded in 1988, the company is headquartered in Plano, USA, with a team of 10001+ employees. The company is currently Late Stage.

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