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Ai Rag Jobs in Deerfield, IL (NOW HIRING)

Neshent Technologies

Applied AI Architect

Norridge, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Hines, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Palatine, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Hillside, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Evanston, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Chicago, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Cicero, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Itasca, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Chicago, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Glencoe, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Oak Park, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

Neshent Technologies

Applied AI Architect

Northlake, IL · On-site

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

New

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All JobsAi Rag JobsAi Rag Jobs in Deerfield, IL

Ai Rag information

See Deerfield, IL salary details

$32.5K

$59.2K

$84.9K

How much do ai rag jobs pay per year?

As of Aug 21, 2026, the average yearly pay for ai rag in Deerfield, IL is $59,232.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,800.00 and $66,100.00 per year, depending on experience, location, and employer.

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 cities near Deerfield, IL are hiring for Ai Rag jobs?

Cities near Deerfield, IL with the most Ai Rag job openings:

Ai Rag jobs near you
Infographic showing various Ai Rag job openings in Deerfield, IL as of August 2026, with employment types broken down into 74% Full Time, 23% Part Time, 2% Contract, and 1% Nights. Highlights an 63% Physical, 5% Hybrid, and 32% Remote job distribution, with an average salary of $59,232 per year, or $28.5 per hour.

Applied AI Architect

Neshent Technologies

Bloomingdale, IL • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

We are looking for an Applied AI Architect with strong hands-on experience in AI/ML architecture, development, and production deployment. The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems.

Must-Have Technical Skills
  • Strong hands-on experience in AI/ML development and production deployment.
  • Experience with Databricks, MLflow, Unity Catalog, Delta Lake, and model serving.
  • Experience with Azure AI Foundry and modern AI/ML platforms.
  • Strong knowledge of RAG and LLM application architecture.
  • Experience building multi-agent systems and workflows.
  • Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI Agents SDK.
  • Strong Python development skills for production AI/ML applications.
  • Experience with CI/CD, MLOps, and AIOps.
  • Knowledge of LLM/RAG/agent evaluation, observability, tracing, and monitoring.
  • Experience with production debugging and performance optimization.
  • Ability to create reusable AI accelerators, templates, skills, and reference implementations.
Roles & Responsibilities
  • Define and implement AI/ML architecture and solutions.
  • Work closely with engineering and business teams to build and deploy AI models.
  • Design and develop LLM, RAG, and multi-agent solutions.
  • Establish best practices for AI evaluation, deployment, monitoring, and production support.
  • Improve and standardize applied AI delivery patterns.
  • Accelerate AI adoption through reusable components, templates, and reference architectures.
  • Provide technical leadership and guidance to AI/ML engineering teams.

Apply