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Remote Rag Jobs in Goodyear, AZ (NOW HIRING)

Strategic Staffing Solutions

Software Engineer

Chandler, AZ · On-site +1

$65 - $85/hr

... Remote is NOT an Option) Duration: 6+ months Job ID: 247270 Required Qualifications: Demonstrable skills (recent) using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG ...

Bex Partners

Automation Engineer

Phoenix, AZ · On-site +1

Support the development of AI-powered features including RAG over documentation, AI-assisted ticket ... Phoenix-based hybrid environment preferred, with fully remote options considered for the right ...

Mondo

Data Scientist

Phoenix, AZ · Remote

$65 - $75/hr

Remote (Candidate must reside in Pacific, Mountain, or Central time zone. Eastern time zone and ... Design and deploy end to end RAG solutions and autonomous AI agents in cloud and enterprise ...

Aprio

Senior AI Product Associate, IT

Phoenix, AZ · On-site +1

$104K - $160K/yr

Exposure to agentic AI workflows, RAG architectures, or LLM integration patterns. * Familiarity ... remote and hybrid options What's in it for you: - Working with an industry leader : Be part of a ...

Epiq

Lead AI Software Engineer

Phoenix, AZ · Remote

Experience with MCP servers, agentic frameworks, and Retrieval-Augmented Generation (RAG). * Strong ... LI-Remote The Compensation range for this role is 120,000 to 170,000 USD annually and may be ...

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Remote Rag information

See Goodyear, AZ salary details

$16

$21

$23

How much do remote rag jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for remote rag in Goodyear, AZ is $21.01, according to ZipRecruiter salary data. Most workers in this role earn between $17.60 and $22.31 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Rag, and why are they important?

I'm sorry, but 'Remote Rag' does not appear to be a recognized professional occupation. Please provide a valid job title.

What is a Remote RAG (Retrieval-Augmented Generation) specialist?

A Remote RAG specialist is a professional who works with Retrieval-Augmented Generation (RAG) systems, typically in the field of artificial intelligence and machine learning. RAG combines traditional information retrieval techniques with generative models like large language models to provide more accurate and contextually relevant answers to user queries. Remote RAG specialists often build, fine-tune, and maintain these systems while working from a remote location. They may also work on integrating RAG models into applications, improving retrieval accuracy, and customizing outputs based on user needs.

What are some common challenges faced by professionals working in a remote RAG (Responsible AI Governance) role?

Professionals in remote RAG roles often encounter challenges related to cross-functional collaboration and maintaining clear communication, especially when working across different time zones. Ensuring alignment on ethical AI standards and compliance requirements can be complex, as it typically involves coordinating with data scientists, legal teams, and business stakeholders. Staying current with evolving regulatory frameworks and best practices in AI governance is also essential, demanding continuous learning and adaptability. Building trust and rapport within a remote team can require extra effort, but leveraging digital collaboration tools and regular check-ins can help mitigate these challenges.
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Remote Rag jobs near you
AI Application Engineer

AI Application Engineer

Advantest

Chandler, AZ • On-site, Remote

Full-time

Posted 11 days ago

Job description

Job Description

  • This role sits at the intersection of semiconductor test engineering and AI, driving the transformation of traditional test workflows into AI-powered systems.
  • As a member of the US AI R&D team, you will work closely with 93K R&D engineers, AI engineers, and data scientists to define, develop, and deploy next-generation AI capabilities for the V93000 platform.
  • As an AI Application Engineer, you will act as the bridge between semiconductor test engineering workflows and AI systems, enabling step-change improvements in productivity such as:
    • test program generation
    • debug and root cause analysis
    • knowledge-driven engineering workflows
  • You will lead customer engagements for AI solutions, serving as the primary interface for:
    • use case discovery
    • product definition
    • feedback and iterative improvement
    • rollout and adoption of new capabilities
  • You will collaborate with global R&D teams to influence product direction and strategy for AI-enabled test solutions.
  • You will design and execute pre-sales and proof-of-concept activities, including:
    • customer demos
    • benchmark studies
    • pilot deployments
  • You will stay current with advances in AI/ML (e.g., LLMs, RAG, agent workflows) and drive internal and external enablement through workshops and training.

Technical Environment

You will work in a hybrid environment combining:

  • Linux-based systems (e.g., Red Hat Enterprise Linux)
  • V93000 / SmarTest development ecosystem
  • Modern AI-assisted development workflows, including:
    • AI-enabled IDEs such as VS-Code, Cursor, GitHub Copilot, and Visual Studio Code
    • Markdown-driven prompt and agent design
    • Python-based automation and AI tooling
  • API-driven systems, version control (Git), and integration with AI platforms and services

Requirements

  • Degree in Electrical/Electronics Engineering or equivalent
  • Strong experience as an Application Engineer on the V93000 platform
  • Solid understanding of AI concepts applied to engineering workflows, such as:
    • LLMs
    • retrieval-augmented generation (RAG)
    • automation and code generation
  • Strong software skills (Java and Python), including:
    • test program development
    • scripting or tool development
  • Proven ability to translate customer problems into scalable technical solutions
  • Excellent customer-facing and pre-sales experience
  • Strong debugging, analytical, and problem-solving skills
  • Ability to lead cross-functional projects and drive outcomes
  • High ownership mindset: proactive, self-directed, and execution-focused
  • Comfortable working in global, cross-functional environments
  • Curiosity and drive to stay at the forefront of AI innovation
  • Willingness to travel internationally (20-30%)
  • Candidates throughout the United States are welcome to apply; remote work options may be available.

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