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Rag Developer Jobs in Raleigh, NC (NOW HIRING)

Archgroup

AVP, AI Engineering (Remote - EST)

Raleigh, NC · Remote

$185K - $235K/yr

This role sits at the seam between automation engineering (AE) and implementation engineering (IE ... RAG, MCP / A2A or equivalent agent-to-agent protocols, agentic orchestration frameworks, and the ...

Archgroup

AVP, AI Engineering (Remote - EST)

Raleigh, NC · Remote

$185K - $235K/yr

This role sits at the seam between automation engineering (AE) and implementation engineering (IE ... RAG, MCP / A2A or equivalent agent-to-agent protocols, agentic orchestration frameworks, and the ...

Material Bank

Applied AI Engineer

Raleigh, NC · On-site

About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next ... Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector ...

Redhat

Software Engineer

Raleigh, NC · On-site +1

$135K - $154K/yr

Develop and deploy AI/ML applications and MLOps workflows using Red Hat OpenShift AI, including RAG and Large Language Models (LLMs). * Perform SRE functions and technical support within an ...

Compunnel

Full Stack Engineer

Durham, NC · On-site

JOB SUMMARY Seeking a Senior Software Engineer for an innovation team focused on leveraging new ... RAG experience. • Docker / Kubernetes / Helm. • Java.

Ccube

AI & ML Tech Lead/Architect

Durham, NC · On-site

$150K - $225K/yr

... RAG. Architecture end to end, built systems. We are seeking a highly skilled AI/ML Leader with a ... Familiarity with AI/ML concepts, especially LLMs, prompt engineering, and AI agents. Understanding ...

E-Solutions, Inc.

Gen AI Engineer

Raleigh, NC · On-site

RAG architectures * Prompt engineering & prompt chaining * Conversational AI design patterns * Strong programming experience in Python preferred Preferred Skill and Experience * Experience with ...

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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 Raleigh, NC? For Rag Developer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Rag Developer jobs in Raleigh, NC look for? The top searched job categories for Rag Developer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Rag Developer jobs? Cities near Raleigh, NC with the most Rag Developer job openings:
Rag Developer jobs near you
Senior Machine Learning Engineer III ***Raleigh, NC***

Senior Machine Learning Engineer III ***Raleigh, NC***

LexisNexis

Raleigh, NC • Hybrid

$118K - $219K/yr

Full-time

Posted 23 days ago

LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

161st of 449 rated business services

Job description

Are you looking to develop your Machine Learning Engineer career?

Do you enjoy coaching others to achieve high standards?

This is a full-time position based in Raleigh, NC.

(Hybrid - 3 days in office)

About the Role

We are seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI systems for legal products. This role focuses on how to build and scale-owning system architecture, infrastructure, and productionization of ML/LLM solutions.

You will partner with Data Scientists to turn validated models and prototypes into reliable, high-performance, customer-facing systems.

Key Responsibilities

  • Architect and implement scalable ML/LLM systems in production.
  • Build and deploy LLM applications, including RAG pipelines and agentic systems.
  • Implement hybrid search systems (semantic + lexical) using embeddings and search platforms.
  • Develop and maintain APIs, microservices, and model serving infrastructure.
  • Build data pipelines and streaming systems for large-scale data processing.
  • Define and develop reusable frameworks, libraries, and infrastructure for AI/ML across teams.
  • Optimize systems for latency, scalability, reliability, and cost efficiency.
  • Establish best practices for deployment, monitoring, observability, and CI/CD.
  • Collaborate with Data Scientists to productionize models and integrate into products.
  • Provide technical leadership in system design and engineering standards.

Required Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • Strong experience implementing and scaling production ML/LLM systems.
  • Deep experience with LLM application development, including RAG and prompt orchestration.
  • Strong experience designing and implementing agentic systems using agent frameworks (e.g., LangChain, LangGraph, AutoGen, Google ADK), including orchestration of multi-step workflows in production environments.
  • Strong experience with hybrid search (semantic + lexical), embeddings, and search platforms (e.g., Solr, OpenSearch).
  • Expertise in distributed systems and cloud-native development, including AWS (S3, DynamoDB).
  • Experience with streaming and messaging systems (e.g., Kafka, SQS) and caching (e.g., Redis).
  • Proficiency in Python and experience with systems languages (e.g., Rust, Go, Scala).
  • Experience building scalable APIs (REST/GraphQL).
  • Experience with containerization and orchestration (Docker, Kubernetes).
  • Strong software engineering fundamentals (system design, testing, CI/CD).

Preferred Qualifications

  • Experience with LLM platforms (e.g., ChatGPT/OpenAI, Claude, Gemini, LangChain, Google ADK).
  • Experience with DevOps and infrastructure as code (e.g., Terraform, CloudFormation, Jenkins).
  • Experience with big data technologies (e.g., Spark, Hadoop).
  • Familiarity with graph databases (e.g., Dgraph, Neo4j, Neptune).
  • Experience building high-availability, low-latency systems.
  • Experience in legal or regulatory domains.

Key Competencies

  • Strong system architecture and scalability mindset.
  • Ownership of implementation, performance, and reliability.
  • Ability to translate data science solutions into production systems.
  • Cross-functional collaboration with DS, product, and platform teams.
  • Excellent debugging, optimization, and operational skills.
  • Clear communication of technical designs and trade-offs.

#AIFluent

U.S. National Base Pay Range: $118,300 - $219,800. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

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