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Rag Engineer Jobs in Raleigh, NC (NOW HIRING)

TEKsystems

Principal Data Scientist

Raleigh, NC

$75 - $90/hr

... Engineering, with deep experience in LLM‑based systems. Proven experience building agentic architectures (planner‑executor, tool‑use agents, ReAct‑style reasoning). Strong background in RAG ...

DPR Construction

MLOps Engineer

Raleigh, NC · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Familiarity with semantic search, retrieval-augmented generation (RAG), or embedding pipelines

DPR Construction

MLOps Engineer

Raleigh, NC · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Familiarity with semantic search, retrieval-augmented generation (RAG), or embedding pipelines

Compunnel

Senior Data Scientist

Raleigh, NC · On-site

... Engineers - with a goal to convert as a true Lead. For the contract duration, you will be heavily ingrained in product deployment and build, RAG, and scaling ML production grade systems. Key ...

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Showing results 41-60

All JobsRag Engineer JobsRag Engineer Jobs in Raleigh, NC

Rag Engineer information

See Raleigh, NC salary details

$57.8K

$88K

$149.2K

How much do rag engineer jobs pay per year?

As of Aug 12, 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.

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 job categories do people searching Rag Engineer jobs in Raleigh, NC look for? The top searched job categories for Rag Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Rag Engineer jobs? Cities near Raleigh, NC with the most Rag Engineer job openings:
Rag Engineer jobs near you
Infographic showing various Rag Engineer job openings in Raleigh, NC as of August 2026, with employment types broken down into 87% Full Time, 7% Part Time, and 6% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $87,979 per year, or $42.3 per hour.

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

RELX

Raleigh, NC • Hybrid

$118K - $219K/yr

Full-time

Re-posted 22 days ago

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.

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