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Rag Llm Jobs in Indiana (NOW HIRING)

Elevate Ventures

Full‑Stack AI Engineer

Indianapolis, IN · On-site

$120 - $180/hr

Develop and optimize LLM-powered workflows including RAG patterns, embeddings, multi‑agent orchestration, and context management. * Architect and maintain infrastructure -- CI/CD, Kubernetes, cloud ...

Deloitte

AI Engineer Consultant

Indianapolis, IN · Hybrid

Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry. * Deliver governed datasets and feature ...

Coforge

DDCS Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

Implement RAG (Retrieval-Augmented Generation) solutions using document chunking, embeddings ... Integrate Azure OpenAI/LLM APIs into enterprise AI search and knowledge retrieval solutions.

The AES Group

Microsoft Fabric Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

Develop partner data ingestion workflows leveraging OCR, LLM-based extraction, confidence scoring ... Integrate Azure OpenAI (or equivalent) services into retrieval-augmented generation (RAG) solutions ...

inKind

Data Engineer

Austin, IN · On-site

$135K - $155K/yr

... generation (RAG) systems. Responsibilities: * Responsible for the design, deployment, and ... Proficiency in Python and modern AI/ML tooling and experience integrating with LLM APIs (Anthropic ...

Deloitte

Google AI Architect

Indianapolis, IN · On-site

... LLM solutions with Gemini on Vertex AI (prompt/tool/function calling, safety policies, Vector Search, evaluation); implement deployment, inference optimization, and monitoring. * Build RAG and ...

Deloitte

Google AI Lead Architect

Indianapolis, IN · On-site

$52.75 - $72.50/hr

... LLM solutions with Gemini on Vertex AI (prompt/tool/function calling, safety policies, Vector Search, evaluation); implement deployment, inference optimization, and monitoring. * Build RAG and ...

Lasting Change, Inc

AI Engineer

Fort Wayne, IN · On-site

... RAG), and tool-use patterns tailored to organizational data and workflows. * Evaluate, select, and integrate best-in-class LLM and AI platform tooling, with preference for Microsoft Fabric, Azure AI ...

Lasting Change Inc

AI Engineer

Fort Wayne, IN

... RAG), and tool-use patterns tailored to organizational data and workflows. * Evaluate, select, and integrate best-in-class LLM and AI platform tooling, with preference for Microsoft Fabric, Azure AI ...

Kobie Marketing

AI Engineer

Indianapolis, IN · On-site

... RAG * Working knowledge of LangChain/LangGraph or a comparable framework like AgentCore Strands, CrewAI, or Semantic Kernel * Experience with LLM observability tools: Amazon CloudWatch, LangSmith ...

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Rag Llm information

What is a RAG LLM?

RAG LLMs, or Retrieval-Augmented Generation Large Language Models, are advanced AI systems that combine the strengths of traditional language models with external data retrieval systems. They work by first searching a relevant database or knowledge base for up-to-date information, and then using a language model to generate responses based on both the retrieved content and their own training. This approach helps LLMs provide more accurate, current, and contextually relevant answers, especially for specialized or rapidly changing topics. RAG LLMs are widely used in customer support, research, and enterprise applications to improve information accuracy and reliability.

How do RAG LLM engineers collaborate with data scientists and product teams to improve retrieval-augmented generation systems?

RAG LLM engineers often work closely with data scientists to fine-tune retrieval mechanisms, optimize model performance, and evaluate system outputs. They also collaborate with product teams to understand user needs, integrate feedback, and ensure the system delivers relevant, accurate information. Regular cross-functional meetings and code reviews are common, fostering a collaborative environment focused on continuous improvement and innovation in response to real-world challenges.

What are the key skills and qualifications needed to thrive as a Retrieval-Augmented Generation (RAG) LLM engineer?

To thrive as a Retrieval-Augmented Generation (RAG) LLM Engineer, you need a strong background in natural language processing, machine learning, and software development, often supported by a degree in computer science or a related field. Familiarity with frameworks like PyTorch, Hugging Face Transformers, vector databases, and cloud platforms, along with experience deploying large language models, is essential. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaboration and innovation in this fast-evolving space. These skills ensure the development of robust, scalable, and accurate retrieval-augmented AI systems that meet real-world information needs.

What is the difference between Rag Llm vs Data Scientist?

AspectRag LlmData Scientist
Required CredentialsTypically a master's or PhD in AI, machine learning, or related fieldsUsually a master's or PhD in data science, statistics, or computer science
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics, research, tech firms, consulting
Industry UsageAI research, natural language processing, machine learning projectsData analysis, predictive modeling, data-driven decision making

Rag Llm and Data Scientist roles often overlap in AI and data analysis fields, but Rag Llm focuses more on language models and AI research, while Data Scientists handle broader data analysis and modeling tasks. Both require advanced degrees and work in tech-driven environments, but their core responsibilities differ in scope and application.

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Rag Llm jobs near you
Infographic showing various Rag Llm job openings in Indiana as of August 2026, with employment types broken down into 100% Part Time. Highlights an 60% In-person, and 40% Remote job distribution.

.NET Full Stack Developer with AI (C#, Angular & LLM Integration) - Q3 - 2026

R2 Technologies Corporation

Indianapolis, IN • On-site

Full-time

Posted 19 days ago

Job description

Overview:
About R2 Technologies: R2 Technologies is a Certified Minority Business Enterprise (MBE) headquartered in Alpharetta, GA. With over two decades of experience across global markets, we provide IT staffing and digital product engineering services to clients ranging from startups to Fortune 1000 companies. In addition to talent services, R2 develops proprietary solutions including SmartEnt, an enterprise AI and IoT intelligence platform. We work closely with our clients to deliver technology outcomes that are realistic, measurable, and impactful.
Job Summary: The .NET estate inside most enterprises is where AI has to land to be useful, and the Microsoft stack now has a first-class path to get it there. R2 Technologies is seeking a .NET Full Stack Developer with AI experience to build and maintain enterprise applications that embed Generative AI capabilities. You will work across .NET Core services, Angular front ends, and SQL Server data layers, integrating LLM-powered features such as document search, retrieval-augmented generation, chatbots, and intelligent workflow automation using Azure OpenAI and Semantic Kernel.
Key Responsibilities:
  • Design, develop, and maintain full stack applications using .NET Core/.NET 8, C#, Angular, and SQL Server.
  • Integrate Generative AI capabilities into enterprise applications using Azure OpenAI, Semantic Kernel, or Python-based LangChain services.
  • Build AI-powered features including chatbots, document search, RAG workflows, and intelligent process automation.
  • Develop and consume RESTful APIs and microservices that connect Angular front ends to backend AI services.
  • Design and optimize database schemas, stored procedures, and data models in SQL Server, and implement vector search using Azure AI Search or comparable stores.
  • Implement security best practices, coding standards, unit testing, and CI/CD pipelines within Agile/Scrum delivery.

Qualifications:
  • 3 years of full stack development experience with hands-on Generative AI or LLM integration work.
  • Strong expertise in C#, .NET Core/ASP.NET Core, Angular (v12+), and SQL Server.
  • Experience integrating LLMs such as Azure OpenAI, OpenAI, or Anthropic Claude into enterprise applications.
  • Hands-on experience with Semantic Kernel, LangChain, or comparable AI orchestration frameworks.
  • Proven experience developing REST APIs and microservices, with a strong grasp of object-oriented design patterns.
  • Familiarity with vector databases such as Azure AI Search, Pinecone, or ChromaDB, and deployment on Azure Cloud.

Skills:
.NET Core,C#,Angular,SQL Server,Generative AI,Azure OpenAI,LLM Integration,REST APIs,Full Stack Development

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