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Ai Rag Jobs in Cary, NC (NOW HIRING)

Envestnet

Lead Data Engineer

Raleigh, NC · 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 ...

Envestnet

Lead Data Engineer

Raleigh, NC · 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 ...

Northern Base

AI Solution Lead

Cary, NC · On-site

... RAG), embeddings, vector databases, prompt engineering, and context engineering ✔ Experience packaging, deploying, serving, and monitoring AI/ML models for real-time and batch inference ✔ Hands ...

Material Bank

Applied AI Engineer

Raleigh, NC · On-site

Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. * Build multimodal AI workflows ...

LexisNexis

Responsible AI Governance Specialist

Raleigh, NC · On-site

$15.75 - $21/hr

Document explainability and transparency practices, including Agentic AI and RAG architecture, Agentic RAG workflows, source citations, Shepard's validation, reasoning workflows, and grounding in ...

IQVIA, Inc.

AI Solutions Architect (Remote)

Durham, NC · On-site +1

$61 - $80.25/hr

Design and implement solutions using foundation models, large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI frameworks * Define approaches for model selection ...

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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:
Ai Rag jobs near you
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.

Principal Technical Product Owner - AI Platform

First Citizens Bank

Raleigh, NC • On-site

Full-time

Re-posted 3 days ago

First Citizens Bank rating

7.4

Company rating: 7.4 out of 10

Based on 106 frontline employees who took The Breakroom Quiz

108th of 170 rated banks

Job description

Overview
The Technical Product Owner is a highly visible principal-level product leader, responsible for driving the successful delivery and adoption of enterprise AI initiatives, platforms, and solutions. This role combines product ownership, technical acumen, and program execution to translate business opportunities into scalable AI capabilities that deliver measurable value.
The role partners closely with business stakeholders, architects, engineering teams, data teams, security, governance, and platform providers to define requirements, prioritize roadmaps, manage delivery, and ensure successful implementation of AI-powered solutions. This individual serves as the bridge between strategy and execution, ensuring AI initiatives progress from concept to production while aligning with enterprise architecture, security, and governance standards.
Responsibilities
AI Product Strategy & Delivery
  • Own the end-to-end delivery lifecycle for AI initiatives, platforms, and use cases.
  • Partner with business stakeholders to identify, evaluate, and prioritize AI opportunities.
  • Translate business objectives into actionable product roadmaps, epics, user stories, and delivery plans.
  • Define MVPs, phased releases, and adoption strategies for Data & AI solutions.
  • Drive execution across multiple initiatives simultaneously while managing dependencies, risks, and timelines.
  • Establish success metrics and KPIs to measure business value and platform adoption.

AI Use Case Enablement
  • Lead discovery, requirements gathering, and solution definition for AI use cases across the enterprise.
  • Facilitate workshops with business and technology stakeholders to refine use case scope and expected outcomes.
  • Support use case evaluation, feasibility analysis, and prioritization.
  • Coordinate proof-of-concepts, pilots, and production implementations.
  • Ensure AI solutions are aligned with enterprise standards, governance requirements, and business objectives.

Technical Product Ownership
  • Collaborate with architects and engineering teams to define solution requirements and technical capabilities.
  • Develop and maintain product backlogs, user stories, acceptance criteria, and release plans.
  • Internal
  • Participate in architecture reviews, design discussions, and solution planning activities.
  • Understand AI architecture patterns including RAG (Retrieval-Augmented Generation), Agentic AI , Graph RAG, AI Assistants & Copilots, Knowledge Management Platforms, Model Orchestration Frameworks
  • Ensure technical requirements align with scalability, security, reliability, and operational objectives.

AWS & Data Platform Collaboration
  • Partner with cloud, platform, and data engineering teams to deliver AI capabilities leveraging AWS Bedrock, Snowflake Cortex AI, Snowflake Native AI capabilities
  • Coordinate platform onboarding, integration, testing, and production readiness activities.
  • Drive adoption of reusable platform capabilities, patterns, and accelerators.

Stakeholder Management & Governance
  • Serve as the primary liaison between business stakeholders and technology delivery teams.
  • Present roadmap progress, risks, dependencies, and outcomes to leadership.
  • Coordinate with Security, Risk, Compliance, Architecture Review Boards, and AI Governance teams.
  • Ensure AI initiatives comply with enterprise policies and responsible AI practices.
  • Manage vendor engagements, proof-of-concepts, and external partnerships.

Leadership & Best Practices
  • Champion agile product management and iterative delivery practices.
  • Drive alignment across business, architecture, engineering, and governance teams.
  • Promote reuse of AI platform capabilities and enterprise standards.
  • Foster collaboration, transparency, and continuous improvement.
  • Stay informed on emerging AI technologies, market trends, and industry best practices.

Qualifications
Bachelor's Degree and 8 years of experience in Product Management, Scrum, Agile OR High School Diploma or GED and 12 years of experience in Product Management, Scrum, Agile
Preferred Qualifications
  • 8+ years of experience in Product Management, Product Ownership, Program Delivery, Technology Delivery, or related leadership roles.
  • 3+ years of experience delivering AI, Data, Analytics, Cloud, or Digital Transformation initiatives in enterprise environments.
  • Proven ability to lead complex cross-functional programs involving business stakeholders, architecture, engineering, security, and governance teams.
  • Strong understanding of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and emerging AI technologies.
  • Hands-on knowledge of cloud-native architectures and services, preferably AWS, including AI/ML, data, integration, and platform capabilities.
  • Experience working with Agile methodologies, backlog management, roadmap planning, user story development, release management, and product lifecycle processes.
  • Excellent communication, stakeholder management, and executive presentation skills, with the ability to translate business needs into scalable technical solutions.

  • Experience delivering Enterprise AI Platforms or large-scale AI products.
  • Experience with AWS Bedrock, Snowflake Cortex AI, Vector Databases, GraphRAG, and Agentic AI solutions.
  • Experience within Banking, Financial Services, or other regulated industries.
  • Product Owner (CSPO, SAFe POPM) and/or AWS Cloud/AI certifications.

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Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

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