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Ai Rag Jobs Near Me

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Google AI Lead Architect

Columbus, OH · On-site

$53.25 - $73.25/hr

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

... RAG/assistants, and agentic workflow orchestration). * Be the senior business partner for Claims ... Accountable for AI governance and compliance-by-design across the Claims portfolio, partnering with ...

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Ai Rag information

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$32K

$58.2K

$83.5K

How much do ai rag jobs pay per year?

As of Jul 19, 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.
What cities are hiring for Ai Rag jobs? Cities with the most Ai Rag job openings:
What states have the most Ai Rag jobs? States with the most job openings for Ai Rag jobs include:
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

Posted 12 days ago


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.