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Rag Developer Jobs in Kentucky (NOW HIRING)

$106K - $127K/yr

Prepare governed, discoverable, and high-quality data that powers LLM, RAG, vector-search ... Engineering excellence: Develop, test, deploy, monitor, and document production-grade data ...

$120 - $180/hr

Build retrieval augmented generation (RAG) and hybrid search pipelines to power robust question ... Create prototypes/POCs and conduct design/code reviews to derisk delivery and raise engineering ...

New

$180 - $260/hr

... RAG) applications. * Collaborate closely with product, sales, and marketing teams to architect and ... DevOps, and reporting teams in building a scalable and innovative product. * Promote best ...

New

$98 - $233/hr

... engineering, and evaluation frameworks. • Experience designing and implementing enterprise AI solutions using RAG, Vector Databases, Guardrails, and Human-in-the-Loop approval mechanisms. • ...

New

Senior Applied AI Software Engineer ( AI)

Louisville, KY · On-site +1

$117K - $155K/yr

... RAG, tool use, workflow automation, and personalized assistance. Develop secure, scalable AI ... Minimum 5 years of professional software engineering experience with advanced Python development ...

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Showing results 1-20

Rag Developer information

What is the difference between Rag Developer vs Textile Technician?

AspectRag DeveloperTextile Technician
CredentialsTypically requires a diploma or degree in textiles or related fieldRequires similar qualifications, often with additional certifications in textile testing
Work EnvironmentFactories, textile mills, production plantsLaboratories, quality control departments, manufacturing facilities
Industry UsageUsed in textile manufacturing to develop and process rags for reuse or recyclingInvolved in testing, quality assurance, and technical support in textile production

Both Rag Developers and Textile Technicians work within the textile industry, often in manufacturing settings. Rag Developers focus on creating and processing recycled rags, while Textile Technicians handle testing and quality control. The roles share similar educational backgrounds and work environments, but their specific responsibilities differ based on their focus within textile production.

What are popular job titles related to Rag Developer jobs in Kentucky?

For Rag Developer jobs in Kentucky, the most frequently searched job titles are:

What job categories do people searching Rag Developer jobs in Kentucky look for?

The top searched job categories for Rag Developer jobs in Kentucky are:

What cities in Kentucky are hiring for Rag Developer jobs?

Cities in Kentucky with the most Rag Developer job openings:

Infographic showing various Rag Developer job openings in Kentucky as of August 2026, with employment types broken down into 66% Full Time, and 34% Contract. Highlights an 82% In-person, and 18% Remote job distribution.

Principal Enterprise Architect, AI Health Cloud

BrightSpring Health Services

Louisville, KY • On-site

$218K/yr

Full-time

Re-posted 15 hours ago


BrightSpring Health Services rating

5.1

Company rating: 5.1 out of 10

Based on 63 frontline employees who took The Breakroom Quiz

209th of 240 rated social care providers


Job description

Overview

We are seeking a highly experienced and hands-on Principal Enterprise Architect to lead the full stack design and integration of advanced AI/ML platform and solution architectures within our AI-enabled Health Cloud Platform. This role combines deep expertise in end to end systems architecture, platform engineering, and integration/API design, enabling seamless, secure, and scalable AI/ML healthcare applications.


You will play a critical role in shaping both the technical foundation of the platform and the delivery of intelligent healthcare solutions, ensuring that AI capabilities such as Generative AI, Agentic AI, RPA, and fine-tuned RAG/Vector DB models are effectively embedded into clinical and pharmacy workflows.


Responsibilities

  • Architect and lead the full stack implementation of end-to-end AI/ML platform and solution architectures, ensuring seamless integration with enterprise systems and healthcare data sources.
  • Design and develop robust, scalable APIs and microservices using technologies such as .NET, C#, and RESTful services.
  • Define and enforce platform and integration architecture standards, including data contracts, API security, service orchestration, and interoperability.
  • Collaborate with AI/ML engineers, product managers, API, and data engineers to translate business and clinical requirements into cloud-native, reusable platform capabilities and solution-specific workflows.
  • Architect and optimize LLM-based systems, including RAG pipelines, vector databases, and agentic AI frameworks (e.g., LangChain, AutoGen).
  • Design and evolve the AI/ML platform architecture, including model lifecycle management, orchestration layers, and reusable AI services.
  • Ensure all solutions and platform components are HIPAA-compliant, secure, and aligned with healthcare interoperability standards (FHIR, HL7 etc.).
  • Evaluate and integrate third-party AI services, open-source tools, and cloud-native components into the platform.
  • Provide architectural leadership across model training, deployment, monitoring, and retraining, ensuring scalability and performance.

Qualifications

  • 10+ years of experience in solution and platform architecture, with a strong focus on AI/ML systems and enterprise integration.
  • 15+ years in overall solution architecture.
  • Proven experience designing and delivering AI-powered healthcare or pharmacy platforms and solutions.
  • Experience with multi-agent systems, RPA tools, and intelligent automation in healthcare.
  • Strong experience with API development and integration using .NET, C#, and modern API frameworks.
  • Deep understanding of cloud platforms (Azure preferred), containerization (Docker, Kubernetes), and MLOps practices.
  • Expertise in Generative AI, RAG architectures, vector databases, and agentic AI orchestration.
  • Expertise in healthcare data standards and secure data handling practices.
  • Excellent communication and stakeholder engagement skills.

Preferred Qualifications:

  • Background in AI/ML engineering, data science, or biomedical informatics.
  • Knowledge of responsible AI, model explainability, and bias mitigation.
  • Advanced degree (MS or PhD) in Computer Science, AI/ML, or a related field.

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