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Ai Rag Jobs in Colorado (NOW HIRING)

Themesoft Inc

Remote_QA tester-AI Agentic

Denver, CO · On-site

$90 - $140/hr

AI Agentic Tester Must have- Experience testing Generative AI, LLM, or AI-based applications ... Validate Retrieval-Augmented Generation (RAG) outputs. * Measure hallucination rates and response ...

BillGO

Senior AI Data Analytics Engineer

Fort Collins, CO · On-site

$132.80 - $196.50/hr

As the architect of the data models, semantic layers, and AI/RAG patterns that Product, Finance, Risk, and Operations all build on, this person turns scattered payments data into a single source of ...

Delan Associates, Inc

AI Agentic Tester

Denver, CO · On-site

$90 - $120/hr

Retrieval-Augmented Generation (RAG) * Prompt Engineering Validation * AI Model Validation & Evaluation * API Testing (Postman, REST APIs, Swagger) * Python * Test Automation (Selenium / Playwright ...

TIFIN

AI Engineering, TIFIN.ai

Boulder, CO

$200K - $275K/yr

Our AI Engineers architect, build, and operationalize these systems at scale, pushing the ... Build agent workflows that integrate RAG-based retrieval, agent memory, and knowledge graphs for ...

Kiewit Corporation

Sr AI Engineer

Lone Tree, CO · On-site +1

$103K - $141K/yr

Design and optimize Retrieval-Augmented Generation (RAG) services and agent-based workflows. * Integrate AI platform services with enterprise data platforms and cloud infrastructure. * Implement ...

TIFIN

AI Engineering, TIFIN.ai

Boulder, CO · On-site

$128K - $168K/yr

Build agent workflows that integrate RAG-based retrieval, agent memory, and knowledge graphs for ... Design and enforce AI governance - audit trails, guardrails, and human-in-the-loop checkpoints ...

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Ai Rag information

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 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 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 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 are popular job titles related to Ai Rag jobs in Colorado?

For Ai Rag jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Ai Rag jobs in Colorado look for?

The top searched job categories for Ai Rag jobs in Colorado are:

What cities in Colorado are hiring for Ai Rag jobs?

Cities in Colorado with the most Ai Rag job openings:

Ai Rag jobs near you
Infographic showing various Ai Rag job openings in Colorado as of August 2026, with employment types broken down into 82% Full Time, 6% Part Time, and 12% Contract. Highlights an 100% In-person job distribution.

Remote_QA tester-AI Agentic

Themesoft Inc

Denver, CO • On-site

$90 - $140/hr

Other

Posted 27 days ago

Job description

Role: AI Agentic Tester

Must have- Experience testing Generative AI, LLM, or AI-based applications.

Keyword:

Skills: Modern Functional Quality Engineering Experience Required: 2-4 Years

PFB the responsibilities and skills needed:

Functional Testing
  • Validate AI agent workflows against business requirements.
  • Test end-to-end AI use cases, including multi-agent interactions.
  • Verify task completion accuracy and output quality.
  • Test agent orchestration, tool calling, and workflow execution.
  • Evaluate LLM responses for accuracy, relevance, and consistency.
  • Test prompt engineering effectiveness and response quality.
  • Validate Retrieval-Augmented Generation (RAG) outputs.
  • Measure hallucination rates and response reliability.
Required Skills
  • 3-8 years of QA/Test Engineering experience.
  • Experience testing Generative AI, LLM, or AI-based applications.
  • Knowledge of AI Agents, Agentic AI, RAG, and prompt engineering.
  • Hands-on experience with API testing (Postman, Swagger, REST APIs).
  • Experience with automation frameworks (Selenium, Playwright, PyTest).
  • Proficiency in Python.
  • Understanding of AI evaluation metrics and testing methodologies Knowledge of Azure OpenAI, AWS Bedrock, Gemini, or similar AI platforms
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