ZipRecruiter

Log In

1

Ai Rag Jobs in Forney, TX (NOW HIRING)

Tanisha Systems

Sr. Generative AI Developer

Dallas, TX · On-site

$120K - $161K/yr

Key Responsibilities Architect and develop Generative AI applications using RAG frameworks for enterprise-scale solutions. Design and implement robust system architectures for AI-driven platforms ...

Alpha Consulting Corp.

Python + AI

Addison, TX · On-site

$48.75 - $67/hr

Responsibilities : • building LLM-based applications • building RAG pipelines • building AI APIs using Python and FastAPI • ML deployment using Docker • ML deployment using Kubernetes • ...

Prophecy Technologies

AI/ML Engineer

Plano, TX · On-site

$109K - $131K/yr

Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures. * Develop REST APIs and microservices using FastAPI, Flask, or similar frameworks to expose AI models.

Emumba Inc.

Senior AI Engineer

Dallas, TX · On-site

$140 - $210/hr

Senior AI Engineer Department: Backend Employment Type: Full Time Location: USA Description We're ... You'll design and ship RAG pipelines, integrate LLMs into real products, and build the backend ...

Emumba

Senior AI Engineer

Dallas, TX · On-site +1

$103K - $142K/yr

Senior AI Engineer Department: Backend Employment Type: Full Time Location: USA Description We're ... You'll design and ship RAG pipelines, integrate LLMs into real products, and build the backend ...

Droisys

Generative AI Engineer

Dallas, TX · On-site

Build Generative AI solutions using technologies like LLMs, RAG, Prompt Engineering, and LangChain/LangGraph. * Develop AI Agents and Semantic Kernels for AI-driven enterprise automation solutions.

Pereview Software

AI Engineer

Dallas, TX

Ready to Apply? Pereview Software is seeking an AI Engineer to join our growing Product and ... Develop andmaintainRetrieval-Augmented Generation (RAG)architecturesusing vector databases and ...

Upbound

AI Cybersecurity Engineer

Plano, TX

AI Cybersecurity Engineer Who We Are At Upbound Group, we are committed to elevating financial ... Harden RAG pipelines against retrieval manipulation attacks, indirect prompt injection via poisoned ...

Upbound Group, Inc.

AI Cybersecurity Engineer

Plano, TX · On-site

AI Cybersecurity Engineer Who We Are At Upbound Group, we are committed to elevating financial ... Harden RAG pipelines against retrieval manipulation attacks, indirect prompt injection via poisoned ...

Upbound

AI Cybersecurity Engineer

Plano, TX

AI Cybersecurity Engineer Who We Are At Upbound Group, we are committed to elevating financial ... Harden RAG pipelines against retrieval manipulation attacks, indirect prompt injection via poisoned ...

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 ...

Wise Skulls

Sr. AI Technology Architect

Irving, TX · On-site

Key Responsibilities • Define and govern enterprise AI architecture including LLMs, RAG, Agentic AI, and Edge AI systems. • Establish reference architectures for cloud-native AI, GPU-based ...

previous page

Showing results 41-60

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 Aug 16, 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?

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.

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 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 job categories do people searching Ai Rag jobs in Forney, TX look for?

The top searched job categories for Ai Rag jobs in Forney, TX are:

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

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

Ai Rag jobs near you
Infographic showing various Ai Rag job openings in Forney, TX as of June 2026, with employment types broken down into 22% Full Time, 67% Part Time, 1% Temporary, and 10% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution, with an average salary of $52,471 per year, or $25.2 per hour.

AI Platform Engineer

Accord Technologies Inc.

Dallas, TX • On-site

Contractor

Re-posted 23 days ago

Job description

AI Platform  Engineer 
Location: Dallas, TX, Charlotte, NC
Position type: W2 contract.
Visa: Any visa independent
 
 
We are looking for an Platform AI Engineer  a builder who can architect the "factory" where AI is made.
Our goal is to build an internal, on-premises AI ecosystem that mimics the capabilities of AWS or Azure. You will be responsible for creating a horizontal platform used by various lines of business to deploy AI projects simultaneously.
Key Responsibilities
  • Platform Architecture: Design and develop a "Model-as-a-Service" platform that allows non-experts to use drag-and-drop components to build AI solutions.
  • RAG-as-a-Service: Build and optimize end-to-end Retrieval-Augmented Generation (RAG) pipelines, including sophisticated chunking strategies and vector database management.
  • Tooling & Libraries: Develop and maintain MCP (Model Control Protocol) libraries, clients, and servers to connect various data sources to the AI engine.
  • Infrastructure Management: Help manage and optimize one of the largest on-premise GPU farms in the U.S. banking sector (500+ Nvidia nodes).
  • Agentic AI: Build a repository for Agentic AI where users can select existing agents or build custom ones for specialized tasks.
  • CI/CD Integration: Integrate AI deployment pipelines with enterprise-level CI/CD tools like Jenkins and Ansible.
  • Compliance & Guardrails: Implement corporate-level guardrails and work within Model Risk Management (MRM) frameworks to ensure all AI deployments are secure and compliant.
Required Technical Skills
  • Expert Python: Deep, hands-on knowledge is mandatory.
  • Data Engineering: Extensive experience in massive data ingestion and processing.
  • RAG Expertise: Deep understanding of vector databases, inferencing, and advanced chunking strategies.
  • Platform Engineering: Proven experience building tools/platforms that other developers or business units use.
  • Infrastructure Knowledge: Experience mimicking cloud capabilities (AWS/Azure) within a strictly on-premise environment.
  • DevOps: Familiarity with Jenkins, Ansible, and automated deployment pipelines.
 
Experience & Qualifications
  • Seniority: This is a senior-level role. We are looking for someone with a proven track record of building production-grade platforms (10-15+ years)
  • Industry Knowledge: You must stay current with the "latest and greatest" in AI (e.g., rag-less inferencing, agentic frameworks).
  • Problem Solver: Must be able to take a use case from a business unit and translate it into a scalable platform service.
  • Experience with Scale: Experience working with large-scale GPU farms and high-volume data environments is highly preferred.