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Ai Rag Jobs (NOW HIRING)

Group Nine LLC

Data Engineer - Gen AI & RAG

Manhattan, NY · On-site

$126K - $151K/yr

Data Engineer - Gen AI & RAG We are seeking an experienced Data Engineer with strong expertise in Generative AI, RAG architecture, and modern cloud data platforms. The ideal candidate will be ...

MphasiS Corporation USA

Agentic AI Lead

Berkeley Heights, NJ · On-site

$146K - $179K/yr

Agentic AI Lead (Python) Vertex AI RAG + Graph/Vector Datastores Berkeley Heights, NJ Role summary We re looking for a strong agentic AI developer who can build and productionize Vertex AI based RAG ...

Hirekeyz Inc

Agentic AI Developer

Berkeley Heights, NJ · On-site

Berkeley Heights, NJ Duraction: Full Time Agentic AI Developer (Python) -- Vertex AI RAG + Graph/Vector Datastores Role summary We're looking for a strong agentic AI developer who can build and ...

Precision Technologies Corp

AI Engineer

Dallas, TX · On-site

Contract Key Skills - AI, Python, Rag, LLM Overview We are seeking an AI Engineer with proven experience in building and scaling AI-powered applications . This role combines hands-on development with ...

Intellectt INC

AI Software Engineer

Foster City, CA · On-site

RAG Architecture & Vector Databases * AI Agents & Conversational AI * LangChain / LlamaIndex / AutoGen * Backend & API Development * Cloud Technologies (AWS/GCP/Azure) * Docker / Kubernetes ...

IT First Source

Agentic AI Lead

Berkeley Heights, NJ · Hybrid

$146K - $179K/yr

Agentic AI Lead (Python) -- Vertex AI RAG + Graph/Vector Datastores Berkeley Heights, NJ (5 Days Onsite) FTE Senior candidates only with min 10+ years of experience Role summary We're looking for a ...

ReturnPro

AI/ML Engineer

Aventura, FL · On-site

We are expanding our AI/ML capabilities to include generative AI-driven solutions, RAG applications, and predictive models for retail pricing using collected data from multiple sources. We are ...

eTeam

AI/ML Engineer - Generative AI

Manhattan, NY · On-site

Proficiency in technologies like Agentic AI, Gen AI, RAG, Python, Lang Graph, Lang Chain * Design, build, and deploy agentic AI systems using generative AI models, agent frameworks, custom ...

ReturnPro

AI/ML Engineer

Aventura, FL

We are expanding our AI/ML capabilities to include generative AI-driven solutions, RAG applications, and predictive models for retail pricing using collected data from multiple sources. We are ...

Spruce Infotech

Agentic Gen AI Engineer

Alpharetta, GA · On-site

Key Responsibilities • Proficiency in technologies like Agentic AI, Gen AI, RAG, Python, Lang Graph, Lang Chain • Design, build, and deploy agentic AI systems using generative AI models, agent ...

Percient Inc.

AI Lead

Berkeley Heights, NJ · On-site

$146K - $179K/yr

Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking, embeddings, indexing, retrieval, reranking, grounding). * Build agentic workflows (tool use, planning, reflection/guardrails ...

Georgia IT Inc

AI Solution Architect

Chicago, IL · On-site

$65 - $85.50/hr

This role requires deep expertise in Generative AI, RAG architectures, agent orchestration , and cloud-native distributed systems , along with strong stakeholder engagement and strategic leadership ...

Digital Links Inc

AI/ML Engineer

Minneapolis, MN · On-site

This role requires strong expertise in Generative AI, RAG (Retrieval-Augmented Generation), and enterprise integrations. The ideal candidate should be capable of independently delivering scalable AI ...

Digital Links Inc

AI Solution Architect

Princeton, NJ · On-site

$66 - $87/hr

Deep understanding of AI/ML concepts, including natural language processing (NLP), deep learning, generative AI, RAG architectures, and MLOps practices. Cloud Proficiency: Experience with cloud ...

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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 Jun 4, 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 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 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 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 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.

More about Ai Rag jobs
What cities are hiring for Ai Rag jobs? Cities with the most Ai Rag job openings:
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Ai Rag jobs near you
Infographic showing various Ai Rag job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 76% Physical, 5% Hybrid, and 19% Remote job distribution, with an average salary of $58,245 per year, or $28 per hour.

Data Engineer - Gen AI & RAG

Group Nine LLC

Manhattan, NY • On-site

$126K - $151K/yr

Other

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

Job description

Data Engineer – Gen AI & RAG

We are seeking an experienced Data Engineer with strong expertise in Generative AI, RAG architecture, and modern cloud data platforms. The ideal candidate will be responsible for building scalable data pipelines, supporting AI-driven applications, and optimizing enterprise data workflows.

Key Responsibilities:
  • Design, develop, and maintain scalable data pipelines and data architectures
  • Build and optimize large-scale ETL/ELT workflows using Python and PySpark
  • Work extensively with Databricks and Snowflake for enterprise data processing
  • Collaborate with AI/ML teams to integrate RAG and LLM-based solutions into production systems
  • Develop and support data workflows for structured and unstructured data processing
  • Ensure data quality, governance, security, and compliance standards are maintained
  • Monitor, troubleshoot, and optimize existing data pipelines and workflows
  • Create technical documentation for data architecture, processes, and deployments
  • Support cloud infrastructure and automation initiatives
Required Skills:
  • Strong hands-on experience with Python and PySpark
  • Extensive experience with Databricks and Snowflake
  • Good understanding of Retrieval-Augmented Generation (RAG) concepts and AI/ML fundamentals
  • Experience building scalable data pipelines and distributed processing systems
  • Strong knowledge of ETL/ELT, data warehousing, and data modeling concepts
  • Familiarity with cloud environments such as Azure, AWS, or GCP
  • Excellent troubleshooting, analytical, and communication skills
Preferred Skills:
  • Experience with orchestration tools like Airflow
  • Knowledge of vector databases, embeddings, and LLM integrations
  • Understanding of NLP and deep learning concepts
  • Exposure to Infrastructure as Code tools such as Terraform
  • Experience working in enterprise-scale cloud environments

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