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Rag Engineer Jobs in Texas (NOW HIRING)

Overview Seeking an AI Engineer to design, develop, and deploy scalable enterprise AI solutions ... Build and deploy AI/ML, LLM, and RAG-based solutions. * Design secure, scalable AI architectures.

AI Engineer

Fort Worth, TX · On-site

$114K - $150K/yr

Implement Graph RAG solutions by integrating knowledge graphs, entity extraction, relationship ... Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake ...

Contract Key Skills - AI, Python, Rag, LLM Overview We are seeking an AI Engineer with proven experience in building and scaling AI-powered applications . This role combines hands-on development with ...

Gen. AI Engineer

Fort Worth, TX · On-site

$140 - $260/hr

This is a hands-on engineering role focused on building production-ready AI platforms from ... Design and develop enterprise Generative AI applications using LLMs, RAG, Graph RAG, and multi ...

Gen. AI Engineer

Fort Worth, TX · On-site

$97K - $133K/yr

This is a hands-on engineering role focused on building production-ready AI platforms from ... Design and develop enterprise Generative AI applications using LLMs, RAG, Graph RAG, and multi ...

AI/ML Engineer - Remote

Dallas, TX · Remote

$200 - $350/hr

You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications. Key Responsibilities * Design, implement, and ...

New

AI/ML Engineer - Remote

Austin, TX · Remote

$200 - $350/hr

You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications. Key Responsibilities * Design, implement, and ...

New

AI/ML Engineer - Remote

Houston, TX · Remote

$200 - $350/hr

You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications. Key Responsibilities * Design, implement, and ...

New

RAG pipelines: use Hugging Face, LangChain, and Open AI API to architect RAG pipelines and ... AI Engineer with 6-9 years of experience. Hands-on experience in shop floor operations, production ...

We are seeking an AI Engineer to design and deploy production-grade AI solutions across LLM applications, RAG pipelines, retrieval systems, and scalable ML services. This role blends model ...

... RAG architectures. - Build and integrate AI capabilities into .NET applications using C# and ASP ... prompt engineering, AI agents, embeddings, and vector search solutions. - Collaborate with ...

Sr Gen AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Senior Generative AI Engineer (Azure / RAG / LLM) We're looking for a hands-on Senior AI Engineer to build and deploy production-grade generative AI solutions. This role focuses on taking use cases ...

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Showing results 1-20

Rag Engineer information

See Texas salary details

$55.4K

$84.3K

$143K

How much do rag engineer jobs pay per year?

As of Aug 30, 2026, the average yearly pay for rag engineer in Texas is $84,325.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,800.00 and $97,800.00 per year, depending on experience, location, and employer.

What is the difference between Rag Engineer vs Textile Technician?

AspectRag EngineerTextile Technician
Required CredentialsEngineering degree, technical certificationsDiploma or degree in textiles or related field
Work EnvironmentFactories, manufacturing plants, R&D labsTextile mills, production facilities, quality control labs
Industry UsageDesigning and improving rag production processesMonitoring textile quality, testing fabrics

While both roles involve working within the textile industry, a Rag Engineer primarily focuses on the engineering aspects of rag production, process optimization, and machinery, whereas a Textile Technician concentrates on fabric testing, quality control, and ensuring textile standards are met. The roles often overlap in industry settings but differ in technical focus and responsibilities.

How to become a rag engineer?

To become a rag engineer, you typically need a bachelor's degree in engineering, materials science, or a related field. Relevant skills include knowledge of manufacturing processes, quality control, and proficiency with industry tools and equipment; certifications in quality management or safety can also be beneficial. Gaining experience through internships or entry-level positions in manufacturing environments is important for career advancement.

What are popular job titles related to Rag Engineer jobs in Texas?

For Rag Engineer jobs in Texas, the most frequently searched job titles are:

What cities in Texas are hiring for Rag Engineer jobs?

Cities in Texas with the most Rag Engineer job openings:

Infographic showing various Rag Engineer job openings in Texas as of August 2026, with employment types broken down into 90% Full Time, 4% Part Time, 5% Contract, and 1% Nights. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $84,325 per year, or $40.5 per hour.

Database Engineer - RAG Platform Developer

Austin, TX • On-site


Apple
Computer and Electronic Product Manufacturing • 10K+ employees

8.1

Company rating: 8.1 out of 10

Based on 678 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

People enjoy working here

Good employer

Recommended by students


Full-time

Re-posted 26 days ago


Job description

We're seeking a Database Engineer to architect and optimize our large-scale RAG (Retrieval-Augmented Generation) platform that serves our users across all of the Hardware Tech group. This role combines deep database expertise with modern AI/ML infrastructure, enabling design teams to seamlessly onboard and query enterprise-scale datasets. You'll be responsible for database architecture and optimization while also contributing to full-stack GenAI application development.
Description
As a Database Engineer on our team, you will architect and optimize our SQL and vector database infrastructure supporting enterprise-scale design data. You'll lead technical decisions on database architecture, scaling patterns, and technology selection for our RAG platform while designing comprehensive strategies to ensure optimal performance. Working closely with the development team, you'll build and refine data ingestion pipelines that enable design teams across all disciplines to seamlessly onboard their data. You'll collaborate with DevOps/SRE teams to ensure quality of service, proper resource allocation, and system scalability while improving RAG retrieval performance through hybrid search strategies, index tuning, and embedding optimization. In addition to your primary database focus, you'll contribute to full-stack development using Python and JavaScript, monitor database health and performance metrics for our multi-tenant system, and develop and maintain database operations procedures, monitoring, and disaster recovery strategies while driving continuous improvement of retrieval quality, search latency, and overall system reliability. You'll also provide mentorship to other engineers on database best practices and scalable design patterns.
Minimum Qualifications
Proficiency in Python or Javascript.
Production experience deploying and managing vector databases (Milvus, Qdrant, or Weaviate) at scale
Experience with PostgreSQL or MySQL in production environments
Understanding of RAG pipelines, including embedding strategies, chunking, and retrieval optimization
Minimum requirement of BS + 10 years of relevant industry experience
Preferred Qualifications
Understanding of Vector database indexing strategies and tradeoffs
Strong SQL proficiency with deep understanding of query planning, indexing strategies, and optimization techniques
Postgres advanced features (extensions, replication, sharding)
Experience managing large-scale databases serving high-concurrency workloads
Experience with embedding models and LLM integration patterns
Demonstrated experience building or optimizing RAG systems in production environments
Collaborative mindset with ability to mentor engineers and work closely with DevOps/SRE teams
Monitoring and observability tools (Prometheus, Grafana)
Kubernetes experience, particularly with stateful applications and database deployments
Proven ability to make architectural decisions for scalable database systems

Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976


What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

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