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Ai Rag Jobs in Arkansas (NOW HIRING)

AAIT Health

AI Engineer

Little Rock, AR · On-site

Build agentic AI systems that can execute multi-step workflows (e.g., chart review ? summarize ... Implement retrieval-augmented generation (RAG) and clinical knowledge workflows that query patient ...

AAIT Health LLC

AI Engineer

Little Rock, AR · On-site

Build agentic AI systems that can execute multi-step workflows (e.g., chart review ? summarize ... Implement retrieval-augmented generation (RAG) and clinical knowledge workflows that query patient ...

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Ai Rag information

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 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 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 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 are popular job titles related to Ai Rag jobs in Arkansas? For Ai Rag jobs in Arkansas, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Arkansas look for? The top searched job categories for Ai Rag jobs in Arkansas are:
What cities in Arkansas are hiring for Ai Rag jobs? Cities in Arkansas with the most Ai Rag job openings:
Ai Rag jobs near you
Infographic showing various Ai Rag job openings in Arkansas as of June 2026, with employment types broken down into 20% Full Time, 68% Part Time, 1% Temporary, and 11% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.

AI Engineer

AAIT Health

Little Rock, AR • On-site

Full-time

Re-posted 28 days ago

Job description

Description:

About Us


AAIT Health (Advanced Artificial Intelligence Technology Health) is building a modern, HIPAA-compliant Electronic Medical Records (EMR) platform. We’re focused on turning today’s best AI and LLM capabilities into reliable, secure, production-grade workflows embedded directly into the EMR experience, so clinicians and staff can work smarter, faster, and with less administrative burden.


What You’ll Do


  • Build agentic AI systems that can execute multi-step workflows (e.g., chart review ? summarize ? recommend next actions ? draft documentation ? route tasks) with appropriate human oversight.


  • Design and implement tool-using LLM workflows (function calling / tools, retrieval, structured outputs, planner–executor patterns, and guardrails).


  • Integrate AI capabilities into our EMR via backend services and APIs (e.g., .NET Core services, MySQL, and modern frontend clients).


  • Implement retrieval-augmented generation (RAG) and clinical knowledge workflows that query patient context, incorporate medical reference content, and cite sources with traceability.


  • Engineer safety, privacy, and compliance into AI workflows, including PHI-safe processing, audit logs, role-based access, minimum-necessary data, prompt/data redaction, and secure storage.


  • Evaluate and improve quality using automated and human-in-the-loop evaluation (e.g., grounding, hallucination rates, task success, latency, and cost).


  • Deploy and operate AI services in production, including monitoring, rate limiting, fallbacks, caching, incident response, and model/provider switching.


  • Collaborate cross-functionally with product, clinical SMEs, security/compliance, and engineering to ship AI-powered features that users trust.

Role Details


  • Full-time position with presence in the office required.


  • Core schedule: Monday–Thursday 8:00 a.m. to 5:00 p.m. and Friday 8:00 a.m. to 12:00 p.m., with occasional work outside regular business hours as needed.


  • Travel may be required.


  • The position operates in a professional office environment and involves significant time writing, typing, speaking, listening, standing, sitting, walking, and reaching.


  • Operation of standard office equipment, non-CDL motor vehicles, mobile phones, and related technology is expected.
Requirements:

You Might Be a Fit If


  • You have strong software engineering fundamentals and production experience (APIs, testing, debugging, performance).


  • You have hands-on experience building with LLMs (OpenAI/Anthropic/others), including tool/function calling, structured outputs, and retrieval-augmented generation (RAG).


  • You’ve integrated AI into real products (not just notebooks or demos) and understand the tradeoffs of latency, cost, and quality.


  • You can design for reliability with deterministic interfaces, schema validation, retries, fallbacks, and evaluation.


  • You are comfortable working across backend and data, and optionally some frontend integration.


  • You communicate clearly, enjoy collaborating with cross-functional partners, and can explain complex AI behavior to non-technical stakeholders.


  • You are comfortable operating in a startup-like environment, prioritizing impact and iterating quickly while maintaining quality.


Bonus Points


  • Experience in healthcare, EMR, or clinical workflows; familiarity with standards such as HL7/FHIR.


  • Experience with .NET Core, MySQL, and cloud deployment (Azure is a plus).


  • Familiarity with security and compliance practices such as HIPAA and SOC2-style controls, including RBAC and audit logging.


  • Experience building evaluation pipelines (golden datasets, offline eval, red-teaming, prompt regression tests).


  • Experience with vector databases/search or building retrieval layers over relational and document stores.


  • Knowledge of PHI de-identification, redaction, and safe data handling.


Tech Stack


  • Frontend: React + Vite + TypeScript


  • Backend: .NET Core services


  • Database: MySQL


  • Cloud: Azure, AWS


  • AI: LLM APIs, retrieval/vector search, observability & evaluation tooling