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Rag Engineer Jobs in Texas (NOW HIRING)

Sr Gen AI Engineer

Houston, TX ยท 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 ...

AI/ML Engineer

Plano, TX ยท On-site

$109K - $131K/yr

AI/ML Engineer ?? Location: Plano, TX (Hybrid) ?? Duration: Long-Term Contract Client: EmergerTech ... Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures.

AI Solutions Engineer

Dallas, TX ยท On-site

$140 - $170/hr

RAG, Document Intelligence, and AI Platform Patterns: * Implement Retrieval-Augmented Generation ... Strong hands-on engineering capability using Python, REST APIs, Azure services, workflow automation ...

Lead Data Engineer

Lake Dallas, TX ยท On-site

$111K - $133K/yr

Lead Data Engineer Location: Dallas, TX (Onsite) Job Type: Contract Duration: 12 Months Experience ... Design AI-ready data architectures supporting ML, GenAI, RAG, vector databases, and Agentic AI

Fulltime Expertise in LLMs, RAG, vector DBs, cloud architecture, NLP, data engineering, LangGraph, VectorDB, GCP. Solution Architecture & Technical Leadership * Architect end to end GenAI-driven ...

Fulltime Expertise in LLMs, RAG, vector DBs, cloud architecture, NLP, data engineering, LangGraph, VectorDB, GCP. Solution Architecture & Technical Leadership * Architect end to end GenAI-driven ...

RAG Pipeline Security * Harden RAG pipelines against retrieval manipulation attacks, indirect ... Engineer andmaintainnetwork security controls including segmentation andmicrosegmentation, secure ...

RAG Pipeline Security * Harden RAG pipelines against retrieval manipulation attacks, indirect ... Engineer andmaintainnetwork security controls including segmentation andmicrosegmentation, secure ...

RAG Pipeline Security * Harden RAG pipelines against retrieval manipulation attacks, indirect ... Engineer andmaintainnetwork security controls including segmentation andmicrosegmentation, secure ...

RAG & Knowledge Engineering: Vector Databases, PostgreSQL, pgvector, Redis Vector Search, Elasticsearch, Embeddings, Semantic Search, Retrieval Optimization. Workflow Orchestration: LangGraph ...

AI Engineer

Dallas, TX ยท On-site

Develop andmaintainRetrieval-Augmented Generation (RAG)architecturesusing vector databases and ... Collaborate with product managers, engineers, and business stakeholders toidentifyopportunities for ...

RAG & Knowledge Engineering: Vector Databases, PostgreSQL, pgvector, Redis Vector Search, Elasticsearch, Embeddings, Semantic Search, Retrieval Optimization. Workflow Orchestration: LangGraph ...

AI/ML Engineer

Plano, TX ยท On-site

$65 - $75/hr

Hands-on with prompt design, evaluation, LLM orchestration, and RAG implementation patterns ... AWS Solutions Architect, AWS DevOps Engineer, or equivalent industry certifications.

Showing results 21-40

Rag Engineer information

See Texas salary details

$55.4K

$84.3K

$143K

How much do rag engineer jobs pay per year?

As of Sep 4, 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 job categories do people searching Rag Engineer jobs in Texas look for?

The top searched job categories for Rag Engineer jobs in Texas 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, 6% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $84,325 per year, or $40.5 per hour.

Sr Gen AI Engineer

AMSYS Talent

Houston, TX โ€ข On-site

$99K - $137K/yr

Full-time

Re-posted 3 days ago


Job description

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 from concept to production, working closely with product, business, and engineering teams.
This is not a research role-candidates must have real experience building and deploying LLM-based systems in production.
Key Responsibilities
  • Build backend services and APIs for AI-driven applications
  • Develop and integrate LLM solutions (Azure OpenAI / AI Foundry)
  • Design RAG pipelines (embeddings, vector search, retrieval systems)
  • Deploy scalable applications using Docker and Kubernetes (AKS)
  • Translate business use cases into production-ready solutions
  • Optimize performance, cost, and reliability of AI systems
  • Support monitoring and observability of deployed solutions
  • Contribute to agentic workflows and orchestration patterns
Required Skills
  • Strong Python (APIs, async, production systems)
  • Hands-on with LLMs/GenAI (Azure OpenAI, LangChain, Semantic Kernel)
  • Experience with RAG, embeddings, and vector databases
  • API frameworks (FastAPI or similar)
  • Docker + Kubernetes (AKS preferred)
  • Azure or similar cloud experience
  • Strong system design and production deployment experience
Nice to Have
  • Azure AI Search, Pinecone, or similar
  • Agentic AI / orchestration frameworks
  • React/TypeScript (basic UI work)
  • CI/CD and DevOps exposure
What We're Looking For
  • Proven experience shipping AI solutions (not just experimentation)
  • Ownership from prototype โ†’ production
  • Ability to work in fast-paced, client-driven environments
  • Strong communication across technical and business teams