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Ai Rag Jobs in Rosenberg, TX (NOW HIRING)

Deloitte

Google AI Lead Architect

Houston, TX · On-site

$52.75 - $72.25/hr

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Energy transfer

Principal AI Developer

Houston, TX · On-site

Azure OpenAI • Azure AI Foundry • Azure AI Search • Microsoft Copilot Studio • Semantic Kernel • Vector Databases • RAG (Retrieval-Augmented Generation) • Semantic Search • Agentic AI ...

Viridien

Head of Applied AI Products

Houston, TX

Build enhanced RAG (Retrieval-Augmented Generation) systems and AI-assisted research tools. AI Applications & Platforms * Lead the development of AI-native applications and tools. * Implement tool ...

W3Global

Senior Data Scientist

Houston, TX · On-site

Build and deploy RAG (Retrieval-Augmented Generation) systems & AI chat interfaces Work closely with client data science teams (ML/DL ecosystems) Develop GenAI-based enterprise knowledge solutions ...

ACCLiiVE

AI Platform Engineer - Houston

Houston, TX · On-site

AI Platform & Agent Engineer Contract position Houston, TX -Hybrid Required Qualifications ... Experience implementing Retrieval Augmented Generation (RAG), vector search, knowledge management ...

Halliburton

AI/ML Data Engineer - Landmark

Houston, TX · On-site

$109K - $131K/yr

Design and deploy LLM-based solutions (RAG, prompt pipelines, vector search) * Lead architecture decisions for scalable, cloud-native AI platforms * Ensure data governance, security, and responsible ...

Halliburton

AI/ML Data Engineer - Landmark

Houston, TX

$109K - $131K/yr

Design and deploy LLM-based solutions (RAG, prompt pipelines, vector search) * Lead architecture decisions for scalable, cloud-native AI platforms * Ensure data governance, security, and responsible ...

TeamSoft

AI Product Owner

Sugar Land, TX · On-site +1

Experience with custom AI solutions, GenAI, LLMs, RAG, conversational AI, AI agents, intelligent document processing, workflow automation, predictive analytics, or AI-enabled decision support.

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Ai Rag information

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How much do ai rag jobs pay per year?

As of Jul 14, 2026, the average yearly pay for ai rag in Rosenberg, TX is $51,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,700.00 and $58,000.00 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.
What job categories do people searching Ai Rag jobs in Rosenberg, TX look for? The top searched job categories for Ai Rag jobs in Rosenberg, TX are:
What cities near Rosenberg, TX are hiring for Ai Rag jobs? Cities near Rosenberg, TX with the most Ai Rag job openings:
Ai Rag jobs near you
Principal AI Developer

Principal AI Developer

Energy Transfer Equity Lp

Houston, TX • Remote

Other

Retirement, PTO

Posted 11 days ago

Energy Transfer rating

9.0

Company rating: 9.0 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

2nd of 75 rated oil and gas companies

Job description

Energy Transfer, recognized by Forbes as one of America's best large employers, is dedicated to responsibly and safely delivering America's energy.  We are driven to inspire our employees to create superior value for our customers, our investors, a sustainable future and giving back to the community where we have long-standing commitments to causes including MD Anderson Children's Cancer Hospital, The Salvation Army, The American Red Cross, Ronald McDonald House and many more. 

We value all of our employees who make our growth and success possible.  We are proud to offer industry leading compensation, comprehensive benefits, 401(k) match with additional profit sharing, PTO and abundant career opportunities. 

Come join our award winning over 12,000 strong organization as we fuel the world and each other!

Summary:

Energy Transfer is looking for a hands-on AI Developer with strong expertise in Python or .NET, cloud platforms, and modern data tooling to join our multidisciplinary Enterprise AI team. This developer will work alongside AI engineers/developers and business analysts to build, ship, and iterate on real production AI solutions.

This role is ideal for someone who thrives in a fast-paced environment where they own work end-to-end: prototyping, building, deploying, and refining. Candidates who have come up through a smaller company or startup environment - wearing multiple hats and shipping real systems - will feel right at home.

Technical Environment

Core: Python .NET Azure Databricks (data platform)

AI stack: Azure OpenAI Azure AI Foundry Azure AI Search Microsoft Copilot Studio Semantic Kernel Vector Databases RAG (Retrieval-Augmented Generation) Semantic Search Agentic AI MCP (Model Context Protocol)

Essential Duties and Responsibilities

     Design, develop, deploy, and maintain AI solutions using Python and/or .NET.

     Build AI agents using Microsoft Copilot Studio or the Semantic Kernel Agent Framework.

     Build and optimize cloud-native applications on Azure.

     Work with large-scale data in Databricks.

     Partner with AI engineers/developers and business analysts to turn ideas and experiments into production systems.

     Apply critical thinking to evaluate model performance, troubleshoot complex issues, and improve system efficiency.

     Communicate clearly with both technical and non-technical stakeholders.

     Prototype quickly, test rigorously, and iterate often.

Requirements: Education and/or Experience, Knowledge, Skills & Abilities

To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily. The requirements for this position are listed below:

     Bachelor's degree or equivalent experience, with relevant job experience commensurate with the selected job level (see below).

     Professional experience building production systems with Python or .NET (proficiency in both is a strong plus).

     Strong working knowledge of cloud services and architecture patterns - Azure preferred (or equivalent experience in AWS or GCP, with willingness to ramp on Azure).

     Hands-on experience building RAG (Retrieval-Augmented Generation) pipelines.

     Hands-on experience building AI agents with Microsoft Copilot Studio, Semantic Kernel Agent Framework, or an equivalent agent framework (e.g., LangGraph, AutoGen, CrewAI).

     Hands-on experience with at least two of the following:

    Azure AI Search (or equivalent vector/semantic search platform - Pinecone, Weaviate, pgvector, Elasticsearch with vector, AWS Kendra/OpenSearch)

    Vector databases

    Semantic search

    Agentic AI systems (multi-step reasoning, tool use, orchestration)

     Comfort working with SQL and large-scale data platforms (Databricks experience is a plus, but the syntax is approachable if you know SQL).

     Excellent communication and critical-thinking skills.

     Background in a smaller company or startup environment with significant ownership of technical work.

Required experience is commensurate with the selected job level:

     The Senior Specialist level requires a Bachelor's degree or equivalent experience and 5-8 years of relevant job related experience.

     The Lead Specialist level requires a Bachelor's degree or equivalent experience and 8+ years of relevant job related experience.

     The Principal Specialist level requires a Bachelor's degree or equivalent experience and 10+ years of relevant job related experience.

Preferred Qualifications

     Proficiency in both Python and .NET.

     Direct hands-on experience with Microsoft Copilot Studio and/or Semantic Kernel specifically.

     Hands-on experience with Databricks specifically.

     Practical ML experience (model training, evaluation, deployment).

     Familiarity with Azure AI Foundry (or equivalent - AWS Bedrock, Google Vertex AI) and Azure OpenAI (or equivalent managed LLM service) in production.

     Experience with MCP (Model Context Protocol) or similar agent-tooling standards.

     Natural Gas Pipeline or Energy Industry work experience is a plus.

Working Conditions

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.

     Usually, normal office working conditions.

     This is an on-site role, worked in person at the office 5 days per week during business hours.

     Must be able to remain in a stationary position 50% of the time due to prolonged periods of sitting or standing.

     Occasional overnight travel may be required to other business locations within the company. 

 

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