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Ai Rag Jobs Near Me

Virtusa

AI Architect

Columbus, OH · On-site

Establish standards for prompt engineering, RAG, model selection, and evaluation. Enable self-service AI platforms using cloud ecosystems like Amazon Web Services and Microsoft Azure. Preferred ...

Virtusa

AI Architect

Columbus, OH · On-site

Establish standards for prompt engineering, RAG, model selection, and evaluation. Enable self-service AI platforms using cloud ecosystems like Amazon Web Services and Microsoft Azure. Preferred ...

Virtusa Corporation

AI Architect

Columbus, OH · On-site

Establish standards for prompt engineering, RAG, model selection, and evaluation. Enable self-service AI platforms using cloud ecosystems like Amazon Web Services and Microsoft Azure. Preferred ...

Virtusa

AI Architect

Columbus, OH · On-site

Establish standards for prompt engineering, RAG, model selection, and evaluation. Enable self-service AI platforms using cloud ecosystems like Amazon Web Services and Microsoft Azure. Preferred ...

Citizens

Sr Data Scientist- Generative AI

Columbus, OH · On-site

Design, develop, and deploy production-grade Generative AI solutions using LLMs, RAG frameworks, AI agents, and workflow orchestration platforms. * Build intelligent document processing capabilities ...

Lorven Technologies, Inc.

AI Engineer

Columbus, OH · On-site

Hands-on experience with Generative AI , LLMs (OpenAI, Anthropic, Llama, etc.) , LangChain , and RAG architectures. * Experience building AI-powered applications using vector databases (Pinecone ...

New

Monitise

Director, AI - Cyber Security I

Columbus, OH · On-site

Architect and implement multi-agent and agentic AI frameworks that support enterprise cybersecurity use cases, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings ...

Deloitte

AI Engineer Consultant

Columbus, OH · Hybrid

We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ... Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ...

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How much do ai rag jobs pay per year?

As of Aug 8, 2026, the average yearly pay for ai rag in the United States is $58,245.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $65,000.00 per year, depending on experience, location, and employer.
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A map of the United States highlighting the number of Ai Rag job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Ai Rag job openings in each state, with California having the most at 2 and Hawaii the least at 0.

Tech Lead / Lead Architect - RAG & Agentic AI

HAGNOS TECH LLC

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
Local candidate: locals only
Duration: Long Term Project
Interview Mode: Phone + video
 
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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