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Retrieval Augmented Generation Rag Jobs in Arizona

American Express

AI Engineer III

Phoenix, AZ

$57 - $76.75/hr

Help implement and maintain retrieval-augmented generation (RAG) pipelines over financial data, with an emphasis on correctness and safety. * Contribute to shared AI infrastructure such as LLM ...

Republic Services

Staff Engineer - Agentic AI

Phoenix, AZ · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Hands-on experience integrating, and adapting LLMs into enterprise applications, including expertise in prompt engineering, context engineering, retrieval-augmented generation (RAG), GraphRAG, and ...

Republic Services

Staff Engineer - Agentic AI

Phoenix, AZ · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Hands-on experience integrating, and adapting LLMs into enterprise applications, including expertise in prompt engineering, context engineering, retrieval-augmented generation (RAG), GraphRAG, and ...

Rubin Obs

Principal AI Engineer

Tucson, AZ · On-site

$179 - $226/hr

Lead the development of LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, AI agents, copilots, and other advanced AI solutions. * Establish platform capabilities that enable ...

Wells Fargo

Lead Data Science Consultant

Phoenix, AZ · Hybrid

  • Medical

  • Life

  • Retirement

  • PTO

... Retrieval-Augmented Generation (RAG), embeddings/vector search, document extraction tools (Azure Document Intelligence, Textract, DocAI), LangChain/LlamaIndex, and production MLOps. o Strong SQL ...

Rincon Research Corp

Advanced Analytics Engineer

Tucson, AZ · On-site

$101K - $124K/yr

  • Medical

  • Dental

  • Life

  • Retirement

Experience with large language models (LLMs), retrieval-augmented generation (RAG), vector databases, or AI agent frameworks. * Professional certifications in relevant technical areas Where is the ...

AURA

Principal AI Engineer

Tucson, AZ · On-site

$179K - $226K/yr

Lead the development of LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, AI agents, copilots, and other advanced AI solutions. * Establish platform capabilities that enable ...

RLI Corp.

Sr. Software Engineer (.Net Full Stack)

Peoria, AZ

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Familiarity with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, or AI orchestration frameworks. * Evaluate and implement AI-enabled capabilities within ...

Intel Corporation

Senior AI / Data Science Engineer

Phoenix, AZ · On-site

$105K - $143K/yr

  • Medical

  • Retirement

  • PTO

Experience developing Generative AI applications using Retrieval Augmented Generation (RAG) and Agentic AI architectures. * Experience deploying AI/ML solutions into production environments.

Teaching with Telescopes

Principal AI Engineer

Tucson, AZ · On-site

$179 - $226/hr

Lead the development of LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, AI agents, copilots, and other advanced AI solutions. * Establish platform capabilities that enable ...

RLI Corp.

Sr. Software Engineer (.Net Full Stack)

Tempe, AZ

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Familiarity with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, or AI orchestration frameworks. * Evaluate and implement AI-enabled capabilities within ...

NSF's NOIRLab

Principal AI Engineer

Tucson, AZ · On-site

$179K - $226K/yr

Lead the development of LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, AI agents, copilots, and other advanced AI solutions. * Establish platform capabilities that enable ...

NOAO

Principal AI Engineer

Tucson, AZ

Lead the development of LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, AI agents, copilots, and other advanced AI solutions. * Establish platform capabilities that enable ...

Intel

Senior AI / Data Science Engineer

Phoenix, AZ · On-site

$105K - $143K/yr

  • Medical

  • Retirement

  • PTO

Experience developing Generative AI applications using Retrieval Augmented Generation (RAG) and Agentic AI architectures. * Experience deploying AI/ML solutions into production environments.

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AI Engineer III

American Express

Phoenix, AZ

$57 - $76.75/hr

Full-time

Re-posted 3 days ago

American Express rating

8.6

Company rating: 8.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

23rd of 150 rated financial services

Job description

Joining Amex Tech means discovering and shaping your contribution to something big. Here, you can work alongside talented tech teams and build a unique career with the Powerful Backing of American Express. With a range of opportunities to work with the latest technologies, and a commitment to back the broader engineering community through open source, our mission is to power your success. Because Amex Tech is powered by our technology, our culture, and our colleagues. 

The Technology organization enables and accelerates the company's growth strategies, delivering global capabilities and services in support of Amex's customers and colleagues, while maintaining 24/7 servicing and availability to ensure an uninterrupted, high-quality customer experience. Technology provides the foundation for everything we do in the company while driving differentiation through building and leveraging innovative technology and data insights. 

At American Express, AI is reshaping the future of commerce and redefining the experiences our commercial customers and card members expect. Within Amex Technology, we are building platforms, products, and governance that enable agentic AI systems to operate responsibly and at scale across the enterprise. 

Our focus is on agentic AI development: designing intelligent, adaptive systems that can plan, reason, and act across complex workflows with appropriate levels of autonomy. These systems power autonomous workflows, decision support, and customer-facing experiences-while meeting the high standards for security, explainability, reliability, and compliance required in financial services. 

We partner closely with product, design, and business teams to deliver agentic capabilities that reduce operational friction, improve decision-making, and transform how customers interact, transact, and grow. 


 

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.

As part of Team Amex, you'll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.

What We're Looking For 

  • 4+ years of professional software engineering experience. 

  • Some hands-on experience building or contributing to AI-powered features, LLM-based applications, or applied ML systems (professional or project-based). 

  • Solid engineering fundamentals in at least one backend language (Python, Go, or TypeScript). 

  • Familiarity with APIs, basic cloud concepts, and modern development practices. 

  • Interest in agentic AI systems, autonomy, and AI-assisted development workflows. 

  • Willingness to learn, take feedback, and grow technical ownership over time. 

  • Comfort working in collaborative, cross-functional teams. 

  • A strong customer mindset and curiosity about real-world problem solving. 

Preferred Qualifications 

  • Exposure to LLM tooling, prompt engineering, RAG, or agent frameworks through work, coursework, or personal projects. 

  • Internship or early-career experience in fintech or other regulated environments. 

  • Contributions to open-source projects, hackathons, or side projects related to AI or developer tooling. 

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions. 

As an AI Engineer III - Agentic AI, you will be a hands-on builder contributing to the development of production agentic AI systems that operate on real financial data and serve real customers. 

You will work alongside experienced engineers, product managers, and designers to design, build, and ship AI-powered features, while learning how to operate within a regulated, customer-facing environment. This role offers strong mentorship and opportunities to grow your technical depth in LLMs, agentic systems, and production AI engineering. 

This is not a research-only role. You will write production code, contribute to system design discussions, and help operate what you build after launch, with support and guidance from more senior engineers. 

What You'll Do 

  • Contribute to the design and implementation of LLM-powered and agentic product features. 

  • Build and extend agentic AI workflows that reason over context, call tools, and perform actions under guidance from senior engineers. 

  • Help implement and maintain retrieval-augmented generation (RAG) pipelines over financial data, with an emphasis on correctness and safety. 

  • Contribute to shared AI infrastructure such as LLM services, orchestration components, and evaluation or monitoring tooling. 

  • Participate in operating AI systems in production, including monitoring, debugging, and improving reliability and performance. 

  • Collaborate closely with product and design partners, learning to translate customer needs into technical solutions. 

Technical Environment 

  • We don't hire to a narrow checklist, but candidates should be excited to grow in a modern, enterprise-scale engineering environment with a focus on agentic AI. 

Core engineering stack 

  • Languages: Python, Go, TypeScript 

  • Cloud and infrastructure: AWS and/or GCP, Kubernetes 

  • APIs and services: REST, gRPC 

  • Distributed systems: event-driven architectures, including Kafka 

Agentic AI and ML  

  • Commercial and open-source LLMs integrated into agentic workflows 

  • Tooling for agent orchestration, retrieval-augmented generation, vector storage, and evaluation 

  • Schema validation and structured data handling 

AI-assisted development 

  • Use of AI-assisted and agentic development tools for design, implementation, testing, debugging, and refactoring 

  • Learning how to apply these tools responsibly while maintaining production-quality standards 

  • All systems are built to meet high standards for reliability, security, and auditability, reflecting the responsibility of deploying autonomous AI in a financial services environment. 

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