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Ai Rag Jobs (NOW HIRING)

Qualysoft

$52.75 - $72.75/hr

For a challenging AI and data transformation project with a client in the telecommunications sector, we are looking for an experienced Python Developer - Generative AI / RAG (m/f/d) in Vienna. The ...

eTeam

AI/ML Engineer - Generative AI

Manhattan, NY · On-site

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 ...

Infosys

GEN AI, RAG Engineer

Alpharetta, GA · On-site

We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of ...

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 ...

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 ...

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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 Aug 6, 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?

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.
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Ai Rag jobs near you
Infographic showing various Ai Rag job openings in the United States as of August 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $58,245 per year, or $28 per hour.

AI Engineer (GenAI & RAG)

GG Tech Global

Grand Rapids, MI • On-site

Other

Posted 16 days ago

Job description

Job Title: Lead AI Engineer (GenAI & RAG)Overview / Summary

We are seeking an experienced Python Developer with 10+ years of software engineering experience, including 1+ years of experience with AI/RAG.

Key Responsibilities
  • Lead onsite and offshore development teams.
  • Help the product owner and development team achieve customer satisfaction.
  • Connect with stakeholders to understand customer requirements in detail and translate business requirements for the offshore team.
  • Remove impediments and coach the team on resolving blockers.
  • Help development teams identify and address gaps in the agile framework.
  • Resolve conflicts and issues that occur during project execution.
  • Support the product owner by providing clarifications when needed.
  • Document business meeting requirements and notes, and track and close action items.
Required Qualifications
  • 10+ years of experience in software engineering and/or data science.
  • 1+ years of experience in AI/RAG/ML development roles.
  • Strong knowledge of Retrieval-Augmented Generation (RAG).
  • Knowledge of machine learning, deep learning, and natural language processing (NLP).
  • Knowledge of Azure services.
  • Understanding of APIs, microservices, and distributed systems.
  • Knowledge of vector databases.
  • Understanding of DevOps/CI-CD pipelines for machine learning and AI.
  • Exposure to AI governance and compliance.
  • Good communication skills.

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