1

Ai Rag Jobs in Cary, NC (NOW HIRING)

Architect, Data AI

Durham, NC ยท On-site

$61.50 - $79.25/hr

At least one Generative AI / RAG capability shipped to customers, with measurable adoption and a clear quality bar (groundedness, latency, cost per call).A documented AI/ML strategy and roadmap for ...

Senior Systems Engineer

Raleigh, NC ยท On-site +1

$101K - $139K/yr

... AI/RAG: Understanding of vector databases (e.g., Elasticsearch, Milvus, pgvector), embedding models, and RAG architectures. Familiarity with document processing pipelines, chunking strategies, and ...

Senior AI Technologist

Raleigh, NC ยท On-site +1

$48.75 - $63/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Senior AI Technologist

Raleigh, NC ยท On-site

$48.75 - $63/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Implement AI integration patterns such as retrievalaugmented generation (RAG), tool/function calling, and agentbased workflows into applications and internal tooling. * Create and maintain API ...

Implement AI integration patterns such as retrievalaugmented generation (RAG), tool/function calling, and agentbased workflows into applications and internal tooling. * Create and maintain API ...

Lead Data Engineer

Raleigh, NC ยท On-site +1

$111K - $133K/yr

Gen AI: RAG, Embedding, Agents, LLMs, Parameter Tuning * Cloud Computing: AWS * Tools/Products: Data Science Studio, Alteryx, Jupyter, Tableau, PowerBI * Performance optimization for queries and ...

AI Operations Engineer

Durham, NC ยท On-site

$67K - $90K/yr

About the Role We are seeking an AI Operations Engineer to help support and optimize our next ... Help improve retrieval quality for vector search and RAG pipelines * Assist with evaluation ...

AI Operations Engineer

Durham, NC ยท Hybrid

$67K - $90K/yr

About the Role We are seeking an AI Operations Engineer to help support and optimize our next ... Help improve retrieval quality for vector search and RAG pipelines * Assist with evaluation ...

next page

Showing results 1-20

Ai Rag information

See Cary, NC salary details

$29.6K

$54K

$77.4K

How much do ai rag jobs pay per year?

As of Aug 6, 2026, the average yearly pay for ai rag in Cary, NC is $53,959.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,400.00 and $60,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI researcher?

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.

What is an AI RAG?

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.

What are common challenges faced by AI RAG 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 are popular job titles related to Ai Rag jobs in Cary, NC? For Ai Rag jobs in Cary, NC, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Cary, NC look for? The top searched job categories for Ai Rag jobs in Cary, NC are:
What cities near Cary, NC are hiring for Ai Rag jobs? Cities near Cary, NC with the most Ai Rag job openings:
Infographic showing various Ai Rag job openings in Cary, NC as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $53,959 per year, or $25.9 per hour.

Architect, Data AI

Jaggaer

Durham, NC โ€ข On-site

$61.50 - $79.25/hr

Full-time

Re-posted 19 days ago


Job description

Overview

JAGGAER provides an intelligent Source-to-Pay and Supplier Collaboration Platform that empowers organizations to manage and automate complex processes while enabling a highly resilient, responsible, and integrated supplier base. With 30 years of expertise, we specialize in solving complex procurement and supply chain challenges across various industries.

Our 1,300+ global employees are obsessed with ensuring customers get full value from our products - ultimately enhancing and transforming their businesses. For more information, visit www.jaggaer.com

We are hiring a Architect, Data AIย  to lead the next generation of AI/ML across JAGGAER's Source-to-Pay and Supplier Collaboration platform. You'll set the technical direction across conventional ML, Generative AI, LLMs, Agentic AI, and RAG - and ship those capabilities into products used by 1,300+ enterprise customers and the global supply chains they run.

This is a hands-on technical leadership role. You will architect production-grade AI systems, raise the technical bar across data science and ML engineering, and partner directly with product, engineering, and customer-facing leaders to translate procurement and supply chain problems into measurable AI outcomes - spend intelligence, supplier risk, contract understanding, autonomous sourcing workflows, and beyond.

What Success Looks Like in 12 Months:A production agentic workflow live in the JAGGAER platform, automating a meaningful step of a customer's source-to-pay process.At least one Generative AI / RAG capability shipped to customers, with measurable adoption and a clear quality bar (groundedness, latency, cost per call).A documented AI/ML strategy and roadmap for the function - prioritized against business outcomes, with buy-in from product and engineering leadership.

Principal Responsibilities

Set and own the AI/ML technical strategy for the platform - from model architecture to evaluation, deployment, and monitoring - and rally engineering and product leadership around it. Design, develop, and deploy machine learning models for prediction, classification, clustering, and time-series analysis. Develop Generative AI and LLM-powered solutions, including RAG pipelines for knowledge retrieval and contextual responses. Build and optimize Agentic AI systems capable of multi-step reasoning, tool orchestration, and autonomous workflows. Architect and manage vector database solutions (e.g., Pinecone, Weaviate, FAISS, Milvus) for embeddings, hybrid search, and RAG pipelines. Leverage advanced statistical and data science techniques to extract actionable insights from structured and unstructured datasets. Implement and scale AI/ML pipelines using AWS services (SageMaker, Lambda, API Gateway, Bedrock, S3, EKS). Set the technical bar for the data science / ML function - design reviews, code and model reviews, technical standards, and upskilling peers and engineers around AI/ML best practices. Partner with business, product, and engineering leaders to translate procurement and supply chain problems into measurable AI/ML solutions. Write efficient, modular, and maintainable Python code for modeling, data processing, and deployment. Use advanced SQL for querying, transforming, and analyzing large relational datasets. Establish standards for model evaluation, observability, and responsible AI - including documentation, reproducibility, and guardrails for LLM and agent systems.

Position Requirements

14-15 years of experience in data science / applied ML, including 3-4 years building production Generative AI and Agentic AI systems with LangChain, LangGraph, and LangFlow. Track record of technical leadership without direct reports - setting architecture, driving cross-team alignment, and shipping AI/ML into production at enterprise scale. Proven expertise in conventional ML techniques: regression, classification, clustering, time-series forecasting, and predictive modeling. Proven track record of developing and deploying Generative AI, LLM-based, RAG-based, and Agentic AI solutions. Experience with LangChain, LangGraph, LangFlow, or similar agent frameworks. Strong proficiency in Python for machine learning, data manipulation, and deployment. Advanced SQL skills for working with large relational datasets, including hands-on experience with Snowflake (warehousing, performance tuning, and integration with ML/AI pipelines). Hands-on experience with AWS services (SageMaker, Bedrock, Lambda, EKS, API Gateway, S3). Hands-on experience with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus) as a core component of RAG pipelines. Familiarity with data engineering principles and cloud-based data pipelines. Strong judgment translating ambiguous business problems into concrete AI/ML solutions - and the discipline to know when ML is the wrong tool. Preferred Qualifications (Good-to-Have) Exposure to Model Context Protocol (MCP) for orchestrating AI applications. Background in MLOps/CI-CD pipelines for deploying and monitoring ML models at scale. Familiarity with deep learning frameworks (TensorFlow, PyTorch) for advanced modeling.

What We Offer: At JAGGAER, we are committed to supporting you and your family's well-being. Your health is a priority, and we offer a range of programs to help you stay well and thrive. Ourbenefits include Health, Accidental Insurance, and Term Life. Our Values - T.E.A.MAt JAGGAER, our business is about people. Our products are built on intellectual property, but the real differentiator is the teams behind them-the way we collaborate, innovate, solve problems and deliver for customers. TEAM gives us a common set of expectations for how we work together across products, cultures, and geographies. Transparency - Openness Builds Trust:Candor strengthens relationships, speeds decision-making, and ensures problems are solved together-with customers, teammates, and partners. Entrepreneurial Spirit - Own It, Drive It, Make It:A scrappy, customer-obsessed, problem-solving mindset is at the cornerstone of both organizational and personal growth Accountability - Thumbs In, Not Fingers Out:We take responsibility for ourselves before pointing elsewhere Metrics-Driven Results - Outcomes Over Activities:Data and evidence guide our decisions, help us course-correct quickly, and ensure we're delivering real impact.

EEO:JAGGAER is a proud equal opportunity/affirmative action employer supporting workforce diversity. We do not discriminate based upon race, ethnicity, ancestry, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), marital status, caregiver status, sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, genetic information, military, or veteran status, mental or physical disability, or other applicable legally protected characteristics.ACCESSIBILITY:JAGGAER is committed to providing access and reasonable accommodation to applicants. If you are a qualified individual with a disability or a disabled veteran and you think you may require an accommodation for any part of the recruitment process, please send a request to: hr@jaggaer.com All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.Pay Transparency Nondiscrimination Provision (dol.gov)Know Your Rights: Workplace Discrimination is Illegal (dol.gov)

Employment Type: FULL_TIME