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Rag Developer Jobs in Spring, TX (NOW HIRING)

Fervo Energy Company

Agentic AI Engineer

Houston, TX · On-site

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 ...

Diablo Convoy

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

Kirkland & Ellis LLP.

AI Engineer II

Houston, TX · On-site

$116K - $144K/yr

... generation (RAG) pipelines across enterprise environments. * Quality & Evaluation: Create and ... Develop and enhance automated pipelines for AI delivery using tools like Azure DevOps, GitHub ...

Vallen

AI Platform Engineer

Houston, TX · On-site +1

Own the AI/ML layer on Databricks: feature stores, MLflow experiment tracking and model registry, and RAG/prompt architectural standards * Define and enforce prompt engineering standards and LLM ...

FIRST SERVICE CREDIT UNION

AI Engineer

Houston, TX · On-site

Role: The AI Engineer holds primary responsibility for architecting and implementing FSCU's on ... Designs and builds LLM-based applications, including RAG pipelines, agentic search, and vector ...

FIRST SERVICE CREDIT UNION

AI Engineer

Houston, TX

Role: The AI Engineer holds primary responsibility for architecting and implementing FSCU's on ... Designs and builds LLM-based applications, including RAG pipelines, agentic search, and vector ...

FIRST SERVICE CREDIT UNION

AI Engineer

Houston, TX · On-site

Role: The AI Engineer holds primary responsibility for architecting and implementing FSCU's on ... Designs and builds LLM-based applications, including RAG pipelines, agentic search, and vector ...

Cititec

Artificial Intelligence Engineer

Houston, TX · On-site

... or RAG-based solutions • Experience with Python, SQL, or similar technologies • Exposure to AI/LLMs, prompt engineering, workflow automation, or intelligent tooling • Ability to translate ...

New

NATIONMIND LLC

AI Architect Lead

Houston, TX · Remote

$45 - $50/hr

... engineering, AI Ops, governance, security, and business teams. Core Skills: · AI & Automation · AI Agents · GenAI Applications · RAG Workflows · LLM Platforms (OpenAI, Claude, Azure OpenAI ...

Viridien

Head of Applied AI Products

Houston, TX · On-site

Required : • Strong engineering background (ML engineering, MLOps engineer, or equivalent). • ... RAG, agents, workflows, tool calling). • Solid understanding of data pipelines, system design ...

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Rag Developer information

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or engineering management can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries like technology or finance. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant growth potential.

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 does a RAG engineer do?

A RAG (Red, Amber, Green) engineer develops and maintains systems that use RAG status indicators to monitor project or system health. They often work with data visualization tools, automate status reporting, and analyze performance metrics to support decision-making. Strong skills in data analysis, programming, and understanding of project management are typically required.

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 programming, data analysis, and experience with AI frameworks, and they may involve leadership responsibilities or specialized expertise in cutting-edge AI technologies.

Which 3 jobs will survive AI?

For a Rag Developer, roles that require complex manual craftsmanship, creative problem-solving, and specialized knowledge are more likely to persist despite AI advancements. Jobs involving intricate textile design, custom tailoring, and quality inspection rely on human skills and judgment that AI cannot fully replicate. Developing expertise in these areas, along with staying updated on industry tools, can help ensure job security.
What are popular job titles related to Rag Developer jobs in Spring, TX? For Rag Developer jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Rag Developer jobs in Spring, TX look for? The top searched job categories for Rag Developer jobs in Spring, TX are:
What cities near Spring, TX are hiring for Rag Developer jobs? Cities near Spring, TX with the most Rag Developer job openings:
Rag Developer jobs near you
Infographic showing various Rag Developer job openings in Spring, TX as of July 2026, with employment types broken down into 88% Full Time, and 12% Contract. Highlights an 79% In-person, 5% Hybrid, and 16% Remote job distribution.
Agentic AI Engineer

Agentic AI Engineer

Fervo Energy Company

Houston, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 days ago

Job description

Job Type
Full-time
Description
Fervo is building the most cost-effective, repeatable geothermal power plants in the world. Scaling that mission requires AI-native capabilities that drive measurable impact across drilling, completions, production, geophysics, and power plant operations. The Agentic AI Engineer, within the Data & AI team, designs and ships agentic workflows that turn unstructured knowledge and structured operational data into autonomous capabilities for engineers, operators, and decision-makers in the field.
The Agentic AI Engineer owns the end-to-end delivery of agentic AI use cases - from problem framing and architecture, through prototyping, evaluation, deployment, and iteration in production. Working across Data Engineering, IT Infrastructure, domain SMEs, and business stakeholders, this role establishes reusable patterns for retrieval, semantic grounding, tool integration, and agent orchestration on top of our Azure, Databricks, and Snowflake stack. Success requires strong hands-on engineering depth, sound architectural judgment, and pragmatism about what to ship versus what to defer.
Requirements
Responsibilities
Agentic Workflow Design & Delivery
  • Design and deploy end-to-end agentic AI workflows using planner-worker, orchestrator-executor, multi-agent, and RAG-based architectures
  • Build reusable components and reference patterns for tool routing, state management, error handling, and human-in-the-loop checkpoints
  • Implement robust retrieval pipelines (hybrid search, vector + keyword, graph-aware retrieval) over technical documents, historian data, and operational records
  • Translate domain problems from drilling, completions, production, geophysics, and power plant operations into well-scoped agentic use cases with clear success metrics

Semantic Grounding & Knowledge Integration
  • Build and maintain a semantic layer over our data lake and warehouse using Snowflake Semantic Views and Databricks Unity Catalog Metric Views, making business concepts queryable by both humans and agents
  • Develop and curate knowledge graphs that connect domain entities (wells, pads, assets, equipment, events, documents) and serve as grounding context for LLM reasoning
  • Standardize how agents access enterprise data through Model Context Protocol (MCP) servers and equivalent integration patterns

Evaluation, Observability & Production Operations
  • Establish agent evaluation frameworks including golden datasets, automated regression tests, and structured evals for accuracy, faithfulness, and tool-use correctness
  • Implement tracing, logging, and observability across agent runs to support debugging, cost monitoring, and continuous improvement
  • Build feedback loops that capture user input and convert it into eval cases and prompt/system improvements
  • Support production incidents and platform-level issues impacting deployed agents

Deployment & Enablement
  • Deploy agents as production services on our Azure-native stack (App Service, Container Apps, Functions) with Entra ID SSO, Key Vault-managed secrets, and proper cost controls
  • Build lightweight UIs (Streamlit, Gradio, or React) for agentic applications and internal tools
  • Lead design reviews and cross-functional enablement sessions on agentic AI patterns and best practices

Qualifications
Required
  • Bachelor's or Master's degree in Computer Engineering or Data Science preferred.
  • 2+ years of hands-on experience building and deploying agentic AI or LLM-powered applications in production, not just prototypes or notebooks
  • Strong Python skills, including async patterns, API design with FastAPI, and writing testable, maintainable production code
  • Demonstrated experience with at least one major agent framework: LangChain/LangGraph, LlamaIndex, AutoGen, or Semantic Kernel
  • Working knowledge of LLM APIs and SDKs (Anthropic Claude, OpenAI, Azure OpenAI), including tool use/function calling, structured outputs, streaming, and prompt engineering
  • Experience implementing RAG architectures with vector databases (Azure AI Search, pgvector, Pinecone, Weaviate, Chroma, or similar) and embedding models
  • Experience with agent orchestration patterns including multi-step planning, tool routing, state management, and graceful failure handling
  • Familiarity with Model Context Protocol (MCP) or equivalent standards for tool and context integration
  • Cloud deployment experience on Azure (App Service, Container Apps, Functions, Key Vault, Entra ID), or equivalent in AWS/GCP with willingness to work in our Azure-first environment
  • Strong Git and CI/CD experience, including version control discipline, code review, and automated testing
  • Experience with containerization (Docker) and infrastructure-as-code (Terraform preferred)
  • Strong observability and production operations skills, including structured logging, tracing, cost monitoring, and runbook development

Preferred
  • Experience designing or working with semantic models and semantic layers - Snowflake Semantic Views, Databricks Metric Views, dbt Semantic Layer, Cube, or Power BI semantic models
  • Hands-on experience with knowledge graphs: graph databases (Neo4j, Azure Cosmos DB Gremlin), RDF/SPARQL, ontology design, or graph-augmented RAG
  • Experience with agent evaluation tooling such as LangSmith
  • Experience with our broader data stack: Databricks, Snowflake, Azure Data Lake Storage (ADLS), Azure Data Factory
  • Oil and gas or energy industry experience, including familiarity with drilling, completions, production, geophysics, or industrial historian data
  • Background in time-series data, signal processing, or industrial IoT (MQTT, OPC UA, SparkplugB)

Experience with multimodal models for handling well logs, schematics, or scanned reports
Location
Fervo Energy is headquartered in Houston, TX, with growing offices in Golden, CO, Reno, NV, and Oakland, CA, and Salt Lake City, UT. This position will be eligible for some hybrid work flexibility, but regular in-office presence at the Golden or Houston office will be required
Compensation & Benefits
Fervo provides a comprehensive suite of benefits including medical, dental, vision, life, short-term and long-term disability, flexible paid time off, and paid parental leave. Additionally, Fervo offers an incentive stock options program, a bonus incentive program, and a 401(k) plan with an employer match.
Fervo Energy is providing the compensation range and general description of other compensation and benefits that the company in good faith believes it might pay and/or offer for this position based on the successful applicant's education, experience, knowledge, skills, and abilities in addition to internal equity and geographic location. Expected Salary: $103,152 - $158,588 based on location and experience.
Fervo Energy reserves the right to ultimately pay more or less than the posted range and offer other compensation, depending on circumstances not related to an applicant's sex or other status protected by local, state, or federal law.

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