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Rag Engineer Jobs in Arizona (NOW HIRING)

Lorven Technologies

AI Engineering Leader

Tempe, AZ · On-site

$98K - $129K/yr

This role i not a pure management role - the ideal candidate will actively design, build, and scale AI systems (RAG, agents, evaluation frameworks) while leading engineering initiatives and ...

Perficientcorp Inc

Gen AI Engineer

Phoenix, AZ · On-site

Job Title - Gen AI Engineer Location - Phoenix, AZ Duration: 12+ Months Interview Mode - In-Person Interview Tech Stack - AI / Agentic AI, LLM, RAG, FastAPI, GCP, Flask, Python, SQL, Docker ...

Inficare Technologies

AI Python Engineer

Phoenix, AZ · On-site

Build and enhance AI/ML and GenAI-powered solutions using Python, LLMs, RAG, prompt engineering, and agentic AI frameworks * Develop models for NLP, classification, clustering, anomaly detection, and ...

Advantest

AI Application Engineer

Chandler, AZ · On-site +1

You will stay current with advances in AI/ML (e.g., LLMs, RAG, agent workflows) and drive internal ... Degree in Electrical/Electronics Engineering or equivalent * Strong experience as an Application ...

Advantest

AI Application Engineer

Chandler, AZ · On-site

You will stay current with advances in AI/ML (e.g., LLMs, RAG, agent workflows) and drive internal ... Degree in Electrical/Electronics Engineering or equivalent * Strong experience as an Application ...

Bex Partners

Automation Engineer

Phoenix, AZ · On-site +1

Automation Engineer About the Role: Visory is seeking an Automation Engineer to design, build, and ... Support the development of AI-powered features including RAG over documentation, AI-assisted ticket ...

IntraEdge

Engineer II Premium

Phoenix, AZ

$82K - $110K/yr

... RAG) - Prompt engineering and optimization - Data Modeling - Synthetic Data Generation - Exploratory Data Analysis - Data cleaning and preprocessing - Tokenization and embedding models - Model ...

Staffingine LLC

AIML Engineer

Scottsdale, AZ · On-site

AIML Engineer Job Location: Scottsdale - Arizona - USA Job Type: Contract to Hire * Design and ... Experience with RAG and Supervised Tuning techniques * Strong distributed systems skills and ...

MY DR NOW

Be Seen First

AI & Machine Learning Engineer

Chandler, AZ · On-site

$100K - $110K/yr

... agents, RAG solutions, prompt workflows, and AI-driven automation • Develop scalable Python ... Engineering, or related field • 2-3 years of experience building AI/ML or intelligent software ...

Lorven Technologies

Sr Software Engineer

Phoenix, AZ · On-site

$119K - $157K/yr

Generative AI, LLMs, prompt engineering, and RAG concepts . * AI-assisted software development, testing, documentation, and code review * Will Collaborates with leaders, business analysts, project ...

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All JobsRag Engineer JobsRag Engineer Jobs in Arizona

Rag Engineer information

See Arizona salary details

$55.4K

$84.3K

$143K

How much do rag engineer jobs pay per year?

As of Jul 27, 2026, the average yearly pay for rag engineer in Arizona is $84,346.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,800.00 and $97,800.00 per year, depending on experience, location, and employer.

What does a RAG engineer do?

A RAG engineer specializes in managing and analyzing Red, Amber, and Green (RAG) status indicators to monitor project or system performance. They often work with data visualization tools and reporting systems to identify issues and support decision-making in technical or operational environments.

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.

Which 3 jobs will survive AI?

For a Rag Engineer, roles that require complex manual dexterity, problem-solving in unpredictable environments, or specialized craftsmanship are less likely to be automated by AI. These include skilled trades such as welding, electrical work, and mechanical repair, which depend on hands-on expertise and adaptability. Continuous learning and certification in specialized tools or techniques help ensure job security in evolving technological landscapes.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles may involve leading projects, developing innovative algorithms, and working with large datasets, usually in a corporate or research environment. Compensation at this level reflects significant expertise, experience, and responsibility in the AI field.

What engineers make $500,000?

Senior engineers in specialized fields such as petroleum, aerospace, or software engineering can earn $500,000 or more annually, especially with experience, advanced skills, and leadership roles. High compensation often involves working in high-demand industries, holding advanced certifications, or taking on executive-level responsibilities.
What are popular job titles related to Rag Engineer jobs in Arizona? For Rag Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Rag Engineer jobs in Arizona look for? The top searched job categories for Rag Engineer jobs in Arizona are:
What cities in Arizona are hiring for Rag Engineer jobs? Cities in Arizona with the most Rag Engineer job openings:
Rag Engineer jobs near you
Infographic showing various Rag Engineer job openings in Arizona as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $84,346 per year, or $40.6 per hour.
Only w2 candidate - AI/ML Engineer (F2F interview in Scottsdale, AZ )

Only w2 candidate - AI/ML Engineer (F2F interview in Scottsdale, AZ )

EdgeAll

Scottsdale, AZ • On-site

Other

Posted 19 days ago

Job description

About the Role

We are seeking an experienced AIML Engineer to design, build, and operate AI/ML infrastructure and agentic systems. This role involves developing MCP servers and agents, integrating LLMs, and implementing RAG pipelines for production environments.

Key Responsibilities

  • Design, build and operate MCP servers and MCP agents that host, orchestrate and monitor AI/agent workloads.
  • Develop agentic AI, prompt engineering patterns, LLM integrations and developer tooling for production use.
  • Own deployment, scaling, reliability and cost-efficiency on Kubernetes/Docker and Google Cloud with automated CI/CD
  • Design and implement RAG (RetrievalAugmented Generation) pipelines and integrations with vector stores and retrieval tooling; use LangChain and Langfuse for orchestration, chaining, and observability.

Core Responsibilities

  • Implement and maintain MCP server and agent code, APIs, and SDKs for model access and agent orchestration.
  • Design agent behavior, workflows and safety guards for agentic AI systems.
  • Create, test and iterate prompt templates, evaluation harnesses and grounding/chainofthought strategies.
  • Integrate LLMs and model providers (selfhosted and cloud APIs) with unified adapters and telemetry.
  • Build developer tooling: CLI, local runner, simulators, and debugging tools for agents and prompts.
  • Containerize services (Docker), manage orchestration (Kubernetes/GKE), and optimize nodes, autoscaling and resource requests.
  • Ensure observability: logging, metrics, traces, dashboards, alerting and SLOs for model infra and agents.
  • Create runbooks, playbooks and incident response procedures; reduce MTTR and perform postmortems.
  • Design and maintain RAG workflows: document chunking, embeddings, vector indexing, retrieval strategies, reranking and context injection.
  • Integrate and instrument LangChain for composable chains, agents and tooling; use Langfuse (or equivalent tracing) to capture prompts, model calls, RAG traces and evaluation telemetry.

Required Skills & Experience

  • 5+ years of Strong Software Engineering (Python/NodeJS), system design and production service experience.
  • 2+ years of Experience with LLMs, prompt engineering, and agent frameworks.
  • 2+ years of Experience Practical experience implementing RAG: embeddings, vector DBs and retrieval tuning.
  • 2+ years of Experience with LangChain patterns and with toolchain telemetry (Langfuse or similar) for prompt/model traceability.
  • 5+ years of Experience with Kubernetes, Docker, CI/CD and infrastructureascode experience.
  • 2+ years of Experience with Practical experience with Google Cloud Platform services
  • 2+ years of Experience with Observability, testing, and security best practices for distributed systems.
  • 2+ years of Experience with evaluating and mitigating retrieval/augmentation failures, hallucinations, and leakage risks in RAG systems.
  • Familiarity with vendor and opensource vector stores and embedding providers.
  • Familiarity with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, or ArgoCD).

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