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Retrieval Augmented Generation Jobs in Raleigh, NC

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 ...

IQVIA, Inc.

Senior AI Scientist

Durham, NC · On-site

$88K - $120K/yr

Retrieval-Augmented Generation (RAG) systems * Tool-augmented agents * Knowledge graph + LLM architectures * Implement offline and online evaluation mechanisms, such as: * A/B testing and canary ...

IQVIA

Senior AI Scientist

Durham, NC · Remote

$88K - $120K/yr

Retrieval-Augmented Generation (RAG) systems * Tool-augmented agents * Knowledge graph + LLM architectures * Implement offline and online evaluation mechanisms, such as: * A/B testing and canary ...

RELX

Principal Machine Learning Engineer I

Raleigh, NC

$136K - $252K/yr

You will play a key role in developing enterprise-grade AI systems, including large language model (LLM) infrastructure, retrieval-augmented generation (RAG) pipelines, and autonomous agent ...

GEI Consultants

Data Engineer

Cary, NC

$90K - $150K/yr

Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns. * Implement data quality, validation, and lineage ...

GEI Consultants

Data Engineer

Cary, NC · On-site

$106K - $127K/yr

Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns. * Implement data quality, validation, and lineage ...

DPR Construction

MLOps Engineer

Raleigh, NC

Familiarity with semantic search, retrieval-augmented generation (RAG), or embedding pipelines * Exposure to managing and monitoring ML workloads that support generative AI or advanced analytics use ...

Amphenol TCS

AI Lead

Raleigh, NC · On-site

Working knowledge of generative AI, large language models, copilots, agents, prompt/agent design, retrieval augmented generation (RAG), enterprise search, document intelligence, model evaluation, and ...

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Retrieval Augmented Generation information

What are the typical daily responsibilities of a Retrieval Augmented Generation engineer?

A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.

What is a Retrieval Augmented Generation job?

A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.

What are the key skills and qualifications needed to thrive in the Retrieval Augmented Generation position, and why are they important?

To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Raleigh, NC? The most popular types of Retrieval Augmented Generation jobs in Raleigh, NC are:
What are popular job titles related to Retrieval Augmented Generation jobs in Raleigh, NC? For Retrieval Augmented Generation jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Retrieval Augmented Generation jobs in Raleigh, NC look for? The top searched job categories for Retrieval Augmented Generation jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Retrieval Augmented Generation jobs? Cities near Raleigh, NC with the most Retrieval Augmented Generation job openings:
Retrieval Augmented Generation jobs near you
Infographic showing various Retrieval Augmented Generation job openings in Raleigh, NC as of June 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 75% In-person, and 25% Remote job distribution.
Applied AI Engineer

Applied AI Engineer

Material Bank

Raleigh, NC • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 2 hours ago

Job description

Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials.

About the role

As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production — building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community.

This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems.

We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future.

What you'll do

  • Design, build, and deploy end-to-end AI-powered product experiences from concept through production.
  • Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure.
  • Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling.
  • Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning.
  • Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3.
  • Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform.
  • Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies.
  • Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities.
  • Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability.
  • Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value.

What you'll bring

  • 8+ years of experience building and shipping production software, including significant full-stack engineering experience.
  • Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences.
  • Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling.
  • Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems.
  • Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services.
  • Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience.
  • Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight.
  • Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences.
  • Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste.
  • Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred.
  • Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams.

What you'll get from us:

  • Our people: We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution.
  • Relaxation and Celebrations: Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect).
  • Health Benefits: We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program.
  • Plan for your Retirement: 401(k) eligible after your first 90 day's employed!
  • Giving Back: We sponsor multiple events throughout the year to help out our communities.
  • Growth: We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters!
  • Flexible Work Schedules: With business units and employees across the globe, Material Technologies has embraced a hybrid  working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both.

Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.