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Ai Rag Jobs in Ohio (NOW HIRING)

Diverse Lynx

AI/ ML Engineer

Milford, OH · On-site

The role involves designing and implementing RAG pipelines, integrating AI systems, and establishing performance strategies. Responsibilities : • Architect and deliver end-to-end LLM-powered ...

New

Vertiv Co

AI / ML Platform Engineer

Westerville, OH

The AI / ML Platform Engineer will operate within the Digital organization and play a central role ... Build and Maintain RAG Pipelines: Architect and implement end-to-end Retrieval-Augmented Generation ...

Total Quality Logistics

AI Architect

Cincinnati, OH · On-site

Experience with embeddings, vector databases, RAG patterns, LangChain, Semantic Kernel and MLflow ... AI Strategy & Enterprise Architecture * Evaluate and recommend AI models, APIs and platforms (e.g ...

GARGI TECHNOLOGIES INC

AI / GenAI Engineer

Ohio City, OH · On-site

$97K - $131K/yr

AI / GenAI Engineer (Multiple Openings) Location: Jersey City, NJ / Atlanta, GA / Tampa, FL ... This includes everything from prompt engineering and RAG pipelines to multi-agent orchestration ...

TQL

AI Architect

Cincinnati, OH · On-site

$60.50 - $79.50/hr

Hands-on experience with Azure OpenAI, Azure Machine Learning, Azure AI Search, Microsoft Fabric and Lakehouse architectures Experience with embeddings, vector databases, RAG patterns, LangChain ...

American Financial

AI Platform Engineer

Cincinnati, OH · On-site

The AI Platform Engineer is a hands-on engineering role building and operating the enterprise AI ... RAG and Vectorization * Design and operate retrieval pipelines including chunking, embedding ...

Purple Drive

AI/ ML Engineer

Milford, OH

... RAG architectures, embeddings, and vector databases · Experience with agentic frameworks (e.g ... Integrate AI systems with APIs, backend services, and cloud platforms · Establish evaluation ...

New

giftHEALTH Inc

Lead AI Engineer

Columbus, OH · On-site

$152K - $190K/yr

The Lead AI Engineer drives technical decisions across LLM orchestration, RAG pipelines, and production AI infrastructure, while establishing engineering practices, R&D functions, and growing team ...

Gifthealth

Lead AI Engineer

Columbus, OH · On-site

$152K - $229K/yr

The Lead AI Engineer drives technical decisions across LLM orchestration, RAG pipelines, and production AI infrastructure, while establishing engineering practices, R&D functions, and growing team ...

Gifthealth Inc

Lead AI Engineer

Columbus, OH · Remote

$152K - $190K/yr

The Lead AI Engineer drives technical decisions across LLM orchestration, RAG pipelines, and production AI infrastructure, while establishing engineering practices, R&D functions, and growing team ...

US Bank

Lead AI Platform Engineer

Cincinnati, OH · On-site

$98K - $129K/yr

Retrieval-Augmented Generation (RAG) architectures * Prompt engineering techniques * Agentic AI workflows and orchestration * Build intelligent systems using frameworks such as LangChain, LangGraph ...

AWH

Experienced AI Automation Engineer

Columbus, OH · Remote

$50/hr

RAG pipelines * Prompt regressions across model versions * Tradeoffs between fine-tuning, prompting ... S.-based AI enthusiast to join our team and help develop cutting-edge automation solutions. You'll ...

U.S. Bank

Lead AI Platform Engineer

Saint Bernard, OH · On-site

$94K - $125K/yr

Retrieval-Augmented Generation (RAG) architectures * Prompt engineering techniques * Agentic AI workflows and orchestration * Build intelligent systems using frameworks such as LangChain, LangGraph ...

AWH

Experienced AI Automation Engineer

Columbus, OH · Remote

$50/hr

RAG pipelines * Prompt regressions across model versions * Tradeoffs between fine-tuning, prompting ... S.-based AI enthusiast to join our team and help develop cutting-edge automation solutions. You'll ...

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Ai Rag information

What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?

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 are AI RAGs?

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 some common challenges faced by AI RAG (Retrieval-Augmented Generation) 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 Ohio? For Ai Rag jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Ohio look for? The top searched job categories for Ai Rag jobs in Ohio are:
What cities in Ohio are hiring for Ai Rag jobs? Cities in Ohio with the most Ai Rag job openings:
Ai Rag jobs near you
Tech Lead / Lead Architect RAG & Agentic AI

Tech Lead / Lead Architect RAG & Agentic AI

Alltech Consulting Services, Inc.

Columbus, OH • On-site

$51.50 - $70.75/hr

Other

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

Job description

Job Title: Tech Lead / Lead Architect RAG & Agentic AI

Location: Columbus, OH/ Wilmington, DE 3 days onsite role

Long Term Project

Role Summary:
Lead architecture, design, and delivery of Agentic AI and RAG-based solutions, partnering with customers and internal teams to build scalable, secure, and high-impact AI systems.

Must-Have:

  1. Strong experience in RAG pipelines, embeddings, vector DBs, LLM orchestration, and prompting techniques.
  2. Hands-on expertise in AWS (Lambda, API Gateway, Bedrock, S3, OpenSearch, IAM, VPC, Secrets Manager).
  3. Ability to design end-to-end AI architecture and build PoCs before committing solutions to customers.
  4. Deep understanding of AI guardrails (toxicity, hallucination control), data privacy, and cloud security patterns.
  5. Proven ability to lead from the front, mentor teams, and own delivery under tight timelines and high visibility.
  6. Strong customer communication skills ability to explain architecture, trade-offs, and risks clearly.
  7. Experience handling model evaluation, observability, performance tuning, and cost optimization in production AI systems.
  8. Expertise in API design, microservices integration, and event-driven architectures for AI systems.

Good-to-Have:

  1. Experience with Agentic AI frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel, etc.).
  2. Exposure to marketing domain use cases (campaign optimization, personalization, analytics, insights).
  3. Familiarity with multi-agent orchestration, tool usage (MCP), and human-in-loop workflows.

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