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Ai Rag Jobs in Philadelphia, PA (NOW HIRING)

RELX Group plc

Senior ML Ops Engineer

Philadelphia, PA · On-site

$112K - $179K/yr

About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$112K - $179K/yr

About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA

$112K - $179K/yr

About the role, as a Senior Machine Learning Engineer you'll work onAI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrievalwhile enforcingcontent ...

RELX

Senior ML Ops Engineer

Philadelphia, PA

$112K - $179K/yr

About the role, as a Senior Machine Learning Engineer you'll work onAI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrievalwhile enforcingcontent ...

MRO Corporation

Principal AI Engineer

Norristown, PA · On-site

You will design and build production AI systems - RAG pipelines, LLM integrations, human-in-the-loop workflows, and model quality frameworks - while setting the engineering standards other teams ...

MRO Corporation

Principal AI Engineer

Norristown, PA · On-site +1

$180K - $200K/yr

You will design and build production AI systems - RAG pipelines, LLM integrations, human-in-the-loop workflows, and model quality frameworks - while setting the engineering standards other teams ...

MRO Corporation

Principal AI Engineer

Norristown, PA

$180K - $200K/yr

You will design and build production AI systems -- RAG pipelines, LLM integrations, human-in-the-loop workflows, and model quality frameworks -- while setting the engineering standards other teams ...

Mondo

Applied AI Engineer

Conshohocken, PA · On-site

$75 - $80/hr

Implement agent memory, context management, RAG retrieval strategies, and orchestration patterns to support scalable AI architecture. * Design and deploy reusable AI components, skills, and agent ...

SID Global Solutions

AI Lead Engineer

Exton, PA · On-site

$98K - $130K/yr

Develop RAG-based applications leveraging vector databases and enterprise knowledge sources. * Build scalable APIs and AI microservices using Python, FastAPI, and cloud-native architectures. * Deploy ...

SID Global Solutions

AI Lead Developer

Exton, PA · On-site

$57 - $74.50/hr

Develop RAG-based applications leveraging vector databases andenterprise knowledge sources. * Build scalable APIs and AI microservices using Python, FastAPI, andcloud-native architectures. * Deploy ...

SID Global Solutions

AI Lead Developer

Exton, PA

$57 - $74.50/hr

Develop RAG-based applications leveraging vector databases and enterprise knowledge sources. Build scalable APIs and AI microservices using Python, FastAPI, and cloud-native architectures. Deploy AI ...

Mintex Technology

Founding AI Engineer

Philadelphia, PA · On-site

$180K/yr

Founding AI / ML Engineer Location: Philadelphia, PA (Hybrid -3 days) - Remote Employment Type ... Build agentic orchestration and retrieval workflows, including RAG pipelines, fine-tuning, local ...

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Ai Rag information

See Philadelphia, PA salary details

$32.3K

$58.8K

$84.3K

How much do ai rag jobs pay per year?

As of Aug 6, 2026, the average yearly pay for ai rag in Philadelphia, PA is $58,775.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,400.00 and $65,600.00 per year, depending on experience, location, and employer.

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 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 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 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 are popular job titles related to Ai Rag jobs in Philadelphia, PA? For Ai Rag jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Philadelphia, PA look for? The top searched job categories for Ai Rag jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Ai Rag jobs? Cities near Philadelphia, PA with the most Ai Rag job openings:
Ai Rag jobs near you
Infographic showing various Ai Rag job openings in Philadelphia, PA as of August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $58,775 per year, or $28.3 per hour.

Tech Lead / Lead Architect - RAG and Agentic AI

HAGNOS TECH LLC

Wilmington, DE • On-site

$53.50 - $73.50/hr

Other

Re-posted yesterday

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
Visa: H1B
 
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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