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Rag Engineer Jobs in Raleigh, NC (NOW HIRING)

... RAG), agentic AI, unstructured data, and customer-facing products. The Data Scientist will work closely with Machine Learning Engineers throughout the production lifecycle and provide technical ...

... engineering and end-to-end RAG system development. • Strong experience working with unstructured data, including text and documents, document processing, NLP, embeddings, retrieval, and agentic ...

... RAG implementation, evaluation, validation, and proofing. Strong Python programming skills and excellent communication are essential. The candidate will contribute to customer-facing products and ...

AI Engineer

Cary, NC · On-site

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... RAG), and event-driven patterns. * Maintain and optimize Power BI dashboards that support AI ...

Lead Data Engineer

Raleigh, NC · On-site

$99K - $131K/yr

Wells Fargo is seeking a Lead Data Engineer to join the Enterprise Services Technology (EST ... Experience supporting AI-enabled data services, Generative AI, Retrieval-Augmented Generation (RAG ...

New

Showing results 41-60

Rag Engineer information

See Raleigh, NC salary details

$57.8K

$88K

$149.2K

How much do rag engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for rag engineer in Raleigh, NC is $87,979.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,600.00 and $102,100.00 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 Raleigh, NC?

For Rag Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

What cities near Raleigh, NC are hiring for Rag Engineer jobs?

Cities near Raleigh, NC with the most Rag Engineer job openings:

Infographic showing various Rag Engineer job openings in Raleigh, NC as of September 2026, with employment types broken down into 1% Internship, 83% Full Time, 10% Part Time, and 6% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $87,979 per year, or $42.3 per hour.

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

Raleigh, NC • On-site

LexisNexis
IT Services • 10K+ employees

$118K - $219K/yr

Full-time

Re-posted 26 days ago


Key responsibilities

  • Architect and implement scalable ML/LLM systems in production.

  • Build and deploy LLM applications, including RAG pipelines and agentic systems.

  • Collaborate with Data Scientists to productionize models and integrate into products.


LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz


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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