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Rag Developer Jobs in Houston, TX (NOW HIRING)

Senior AI/ML Engineer

Texas City, TX · On-site

$89K - $122K/yr

Develop Generative AI applications using LLMs, RAG, embeddings, vector databases, and prompt engineering . * Work with frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain ...

Works closely with engineering, business, and leadership teams * Hands-on with AI - real day-to-day usage Duties * Define AI use cases (RAG, automation, agentic workflows) * Translate business needs ...

AI Solutions Architect

Houston, TX · On-site

$120 - $180/hr

Architect and implement Generative AI solutions, including RAG-based workflows. * Write production ... Review code, provide technical guidance, and help engineering teams solve complex implementation ...

The Agentic AI Engineer , within the Data & AI team, designs and ships agentic workflows that turn ... Experience implementing RAG architectures with vector databases (Azure AI Search, pgvector ...

The Agentic AI Engineer , within the Data & AI team, designs and ships agentic workflows that turn ... Experience implementing RAG architectures with vector databases (Azure AI Search, pgvector ...

Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ... DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes ...

LLM Engineer

Houston, TX · On-site

$120K - $130K/yr

We are seeking a detail-oriented LLM Automation Engineer to support AI-driven data analysis ... Python, Hugging Face, Langchain, RAG, AWS * PowerPoint presentation skills

Showing results 21-40

Rag Developer information

What is the difference between Rag Developer vs Textile Technician?

AspectRag DeveloperTextile Technician
CredentialsTypically requires a diploma or degree in textiles or related fieldRequires similar qualifications, often with additional certifications in textile testing
Work EnvironmentFactories, textile mills, production plantsLaboratories, quality control departments, manufacturing facilities
Industry UsageUsed in textile manufacturing to develop and process rags for reuse or recyclingInvolved in testing, quality assurance, and technical support in textile production

Both Rag Developers and Textile Technicians work within the textile industry, often in manufacturing settings. Rag Developers focus on creating and processing recycled rags, while Textile Technicians handle testing and quality control. The roles share similar educational backgrounds and work environments, but their specific responsibilities differ based on their focus within textile production.

What are popular job titles related to Rag Developer jobs in Houston, TX? For Rag Developer jobs in Houston, TX, the most frequently searched job titles are:
What cities near Houston, TX are hiring for Rag Developer jobs? Cities near Houston, TX with the most Rag Developer job openings:
Infographic showing various Rag Developer job openings in Houston, TX as of August 2026, with employment types broken down into 69% Full Time, and 31% Contract. Highlights an 82% In-person, and 18% Remote job distribution.

Senior AI/ML Engineer

Raas Infotek LLC

Texas City, TX • On-site

$89K - $122K/yr

Other

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


Job description

Senior AI/ML Engineer – Job Description

Position: Senior AI/ML Engineer
Experience: 10+ Years
Job Type: W2 Contract 

Job Summary

We are looking for a highly experienced Senior AI/ML Engineer with 10+ years of software engineering and machine learning experience to design, develop, and deploy intelligent, scalable AI/ML solutions. The ideal candidate will have strong expertise in Python, machine learning, deep learning, Generative AI, NLP, cloud platforms, and data engineering, along with hands-on experience taking ML solutions from experimentation through production.

Key Responsibilities
  • Design, develop, and deploy end-to-end machine learning and AI solutions for enterprise applications.

  • Build and optimize predictive models using supervised, unsupervised, and deep learning techniques.

  • Develop Generative AI applications using LLMs, RAG, embeddings, vector databases, and prompt engineering.

  • Work with frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, and LlamaIndex.

  • Develop NLP, text classification, recommendation, forecasting, and anomaly detection solutions as required.

  • Build production-ready AI/ML services and integrate models with enterprise applications through REST APIs and microservices.

  • Develop data preprocessing, feature engineering, model training, validation, and evaluation pipelines.

  • Implement MLOps practices for model deployment, monitoring, versioning, and continuous improvement.

  • Work with cloud-based AI/ML services across AWS, Azure, or Google Cloud Platform.

  • Collaborate with data engineers, software engineers, architects, product teams, and business stakeholders.

  • Optimize models for scalability, performance, accuracy, latency, and cost.

  • Establish responsible AI practices including model monitoring, security, governance, and explainability.

  • Mentor junior engineers and contribute to technical architecture and engineering best practices.

Required Skills
  • 10+ years of experience in software engineering, data science, machine learning, or AI engineering.

  • Strong programming experience with Python.

  • Hands-on expertise in Machine Learning and Deep Learning.

  • Strong knowledge of NLP, Generative AI, LLMs, and transformer-based models.

  • Experience with RAG, embeddings, vector databases, prompt engineering, and LLM evaluation.

  • Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, or LlamaIndex.

  • Strong understanding of SQL and experience working with large datasets.

  • Experience developing and deploying REST APIs / microservices for AI/ML applications.

  • Hands-on experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform.

  • Experience with Docker, Kubernetes, Git, CI/CD, and cloud deployment.

  • Understanding of MLOps, model lifecycle management, monitoring, and model versioning.

  • Strong knowledge of data structures, algorithms, software design principles, and scalable system architecture.

Preferred Skills
  • Experience with Azure OpenAI, AWS Bedrock, Amazon SageMaker, Azure Machine Learning, or Vertex AI.

  • Experience with FAISS, Pinecone, Azure AI Search, OpenSearch, Milvus, or similar vector databases.

  • Knowledge of Kafka, Spark, Databricks, Snowflake, or modern data platforms.

  • Experience building AI agents, Agentic AI, tool calling, and multi-agent systems.

  • Familiarity with LangGraph, Semantic Kernel, MCP, or similar agent frameworks.

  • Experience with model fine-tuning, LoRA/QLoRA, and open-source LLMs.

  • Knowledge of AI security, responsible AI, data privacy, and governance.

  • Experience working in Agile/Scrum environments.

Education

Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field.

Ideal Candidate

The ideal candidate is a hands-on senior engineer who can bridge AI/ML research, software engineering, data engineering, and production deployment. They should be capable of independently designing enterprise AI solutions while also contributing to architecture, technical leadership, and mentoring.