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Ai Rag Jobs in Philadelphia, PA (NOW HIRING)

Techridge, Inc.

AI Product Owner

Wilmington, DE · On-site

In-depth understanding of GenAI/LLMs, prompt engineering, RAG, and AI development workflows. * Domain expertise in credit-card systems, fraud detection, or personalized customer marketing.

Xactus

AI Engineer

Broomall, PA · On-site +1

SUMMARY: The AI Engineer (GenAI Features) specializes in designing, building, and deploying ... RAG & GraphRAG Architecture: Design and implement retrieval-augmented generation systems using ...

Deloitte

Google AI Architect

Philadelphia, PA · On-site

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 ...

BofA Securities

Senior Engineer- Agentic AI

Pennington, NJ · On-site

$105K - $144K/yr

Data, RAG, and Knowledge Graphs: - Define ontology and schema for domain knowledge graphs and ... Proven experience implementing Agentic AI solutions (tooluse orchestration, planning, memory/state ...

Bank of America

Senior Engineer- Agentic AI

Pennington, NJ · On-site

$105K - $144K/yr

Data, RAG, and Knowledge Graphs: - Define ontology and schema for domain knowledge graphs and ... Proven experience implementing Agentic AI solutions (tooluse orchestration, planning, memory/state ...

Photon

Lead AI Engineer | Onsite - Delaware

Wilmington, DE · On-site

$99K - $131K/yr

Own delivery of RAG systems , including vector database selection/topology and knowledgebase design . * Drive delivery of AI agent and multi-agent systems and tool-use/MCP integration patterns. * Own ...

Gap International

AI/LLM Engineer

Springfield, PA · On-site

Your work will involve techniques such as fine-tuning, retrieval-augmented generation (RAG), and ... Design and implement AI systems using Large Language Models (LLMs) to solve enterprise challenges ...

Elsevier

AI Software Engineering Lead

Philadelphia, PA

$136K - $217K/yr

Hands-on experience designing and implementing retrieval-augmented generation (RAG) workflows ... Experience building AI-powered APIs and services for production environments * Ability to govern ...

Photon

Lead AI Engineer | Onsite - Delaware

Wilmington, DE · On-site

$99K - $131K/yr

Own delivery of RAG systems , including vector database selection/topology and knowledgebase design . * Drive delivery of AI agent and multi-agent systems and tool-use/MCP integration patterns. * Own ...

RELX

AI Software Engineering Lead

Philadelphia, PA · On-site

$136K - $217K/yr

Hands-on experience designing and implementing retrieval-augmented generation (RAG) workflows ... Experience building AI-powered APIs and services for production environments * Ability to govern ...

Elsevier

AI Software Engineering Lead

Philadelphia, PA · On-site

$136K - $217K/yr

Hands-on experience designing and implementing retrieval-augmented generation (RAG) workflows ... Experience building AI-powered APIs and services for production environments * Ability to govern ...

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All JobsAi Rag JobsAi Rag Jobs in Philadelphia, PA

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 Sep 8, 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 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 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 September 2026, with employment types broken down into 1% Internship, 74% Full Time, 21% Part Time, and 4% Contract. Highlights an 62% Physical, 5% Hybrid, and 33% Remote job distribution, with an average salary of $58,775 per year, or $28.3 per hour.

Agentic AI Engineer

Wilmington, DE • On-site

K-Tek Resourcing LLC
Recruiting and Staffing Services • 11 - 50 employees
Learn more about K-Tek Resourcing LLCexternal

Other

Posted 13 days ago

Job description

  • 12+ years of software engineering experience with strong expertise in Python, AWS and Typescript.
  • Candidate should be owning end-to-end delivery with minimal supervision.
  • Extensive experience building AI applications using Python (FastAPI, Flask, LangChain/LlamaIndex) and TypeScript (Node.js, NestJS, Express) for backend services, AI agents, and orchestration layers.
  • Strong expertise in Agentic AI architecture, including agent design patterns, multi-agent systems, planning, reasoning, memory management, tool/function calling, and workflow orchestration.
  • Hands-on experience with orchestration frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI Agents SDK, or similar enterprise AI frameworks
  • Hands-on experience designing and implementing Agentic AI solutions, autonomous workflows, and enterprise AI applications.
  • Experience building Retrieval-Augmented Generation (RAG), vector database integrations, tool calling, function calling, and LLM-based applications.
  • Ability to independently own user stories from requirement analysis through development, unit testing, peer reviews, Dev/UAT testing, deployment, and production support.
  • Experience developing scalable APIs, microservices, and cloud-native AI solutions on AWS.
  • Strong understanding of prompt engineering, AI governance, observability, evaluation frameworks, and model optimization.
  • Collaborate with Product Owners, Architects, Data Scientists, and Platform teams to deliver enterprise AI capabilities.
  • Mentor engineering teams and drive engineering excellence across the complete SDLC.
 

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