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Internship Retrieval Augmented Generation Jobs in New York

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

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Internship Retrieval Augmented Generation information

What is an internship in Retrieval Augmented Generation (RAG)?

An Internship in Retrieval Augmented Generation (RAG) is a temporary position, typically for students or early-career professionals, focused on developing or researching AI systems that combine information retrieval with generative models. Interns in this field may work on enhancing how AI models find and use external data sources to generate accurate, context-aware responses. This role often involves tasks such as data preprocessing, implementing retrieval algorithms, fine-tuning language models, and evaluating system performance. It offers valuable hands-on experience with cutting-edge AI technologies and frameworks.

What types of projects or tasks can I expect to work on during an internship in Retrieval Augmented Generation (RAG)?

As an intern in Retrieval Augmented Generation, you can expect to work on projects that involve integrating information retrieval systems with generative AI models. Typical tasks may include curating and preprocessing data sets, developing or fine-tuning retrieval algorithms, evaluating the performance of RAG pipelines, and collaborating with engineers and researchers to improve end-to-end system accuracy. You may also assist in conducting experiments, analyzing results, and documenting findings, all within a collaborative team environment that values innovation and knowledge sharing.

What are the key skills and qualifications needed to thrive as an intern working with Retrieval Augmented Generation (RAG), and why are they important?

To thrive as an intern in Retrieval Augmented Generation, you need a foundational understanding of natural language processing, machine learning concepts, and strong programming skills, often supported by coursework or research in computer science or data science. Familiarity with tools like Python, PyTorch or TensorFlow, and experience with libraries such as Hugging Face Transformers and vector databases are typically required. Strong analytical thinking, curiosity, and effective communication make candidates stand out in collaborative, research-intensive environments. These abilities are critical for developing, evaluating, and improving RAG systems that combine information retrieval with generative models.

What is the difference between Internship Retrieval Augmented Generation vs Internship Data Analyst?

AspectInternship Retrieval Augmented GenerationInternship Data Analyst
Required SkillsKnowledge of AI, NLP, retrieval systems, programmingData analysis, statistical skills, Excel, SQL
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Employer UsageDevelop AI models, improve retrieval systemsAnalyze data trends, generate reports

Internship Retrieval Augmented Generation focuses on developing AI models that combine retrieval systems with language generation, requiring skills in AI and programming. In contrast, an Internship Data Analyst concentrates on analyzing data sets to inform business decisions, emphasizing statistical and analytical skills. Both roles are common in tech and business sectors but serve different functions within organizations.

What are the most commonly searched types of Retrieval Augmented Generation jobs in New York?

The most popular types of Retrieval Augmented Generation jobs in New York are:

What are popular job titles related to Internship Retrieval Augmented Generation jobs in New York?

For Internship Retrieval Augmented Generation jobs in New York, the most frequently searched job titles are:

What job categories do people searching Internship Retrieval Augmented Generation jobs in New York look for?

The top searched job categories for Internship Retrieval Augmented Generation jobs in New York are:

What cities in New York are hiring for Internship Retrieval Augmented Generation jobs?

Cities in New York with the most Internship Retrieval Augmented Generation job openings:

Infographic showing various Internship Retrieval Augmented Generation job openings in New York as of August 2026, with employment types broken down into 67% Full Time, 31% Part Time, and 2% Contract. Highlights an 69% Physical, 3% Hybrid, and 28% Remote job distribution.

Engagement Architect (Agentic AI/RAG)

Jersey City, NJ โ€ข On-site

Lorven technologies
IT Servicesย โ€ขย 51 - 200 employees

$170K - $180K/yr

Full-time

Re-posted 13 days ago


Job description

Job Title: Engagement Architect (Agentic AI / RAG)

Location: New York / New Jersey (Onsite)

Job Type: Full-Time

Experience Required: 12+ Years

Job Summary:

We are seeking an experienced Engagement Architect with expertise in Agentic AI, Retrieval-Augmented Generation (RAG), and Enterprise AI Architecture. The ideal candidate will lead the architecture, design, governance, and implementation of enterprise-scale AI solutions across AWS and GCP while collaborating with technical stakeholders to deliver secure, scalable, and production-ready AI platforms.

Required Skills:
  • 12+ years of IT experience with enterprise architecture.
  • Strong expertise in Agentic AI architecture and RAG (Retrieval-Augmented Generation/Reasoning).
  • Experience with multi-agent orchestration and agent harness design.
  • Hands-on experience in spec-driven development and design-to-code conversion.
  • Strong knowledge of prompt engineering, evaluation engineering, and reasoning frameworks.
  • Experience designing retrieval pipelines, semantic search, and knowledge graph integration.
  • Expertise in AWS and Google Cloud Platform (GCP).
  • Strong understanding of enterprise security architecture, Identity-as-Code, and Policy-as-Code.
  • Experience with design-time and runtime AI governance.
  • Knowledge of React-pattern reasoning loops.
  • Excellent architecture documentation and stakeholder communication skills.
Responsibilities:
  • Lead end-to-end architecture for enterprise Agentic AI solutions.
  • Design and build supervisor, intake, and data-source-level AI agents.
  • Implement multi-agent orchestration and reasoning workflows.
  • Design, optimize, and tune Retrieval-Augmented Generation (RAG) pipelines.
  • Lead prompt engineering and AI model evaluation strategies.
  • Ensure secure, scalable AI architecture aligned with enterprise standards.
  • Oversee design-to-code conversion, implementation reviews, and testing.
  • Create architecture documentation, diagrams, and technical standards.
  • Conduct architecture review sessions and collaborate with engineering teams and client stakeholders.
  • Drive governance, security, and best practices across AI implementations.

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About Lorven technologies

Sourced by ZipRecruiter

Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

2001

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