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Internship Retrieval Augmented Generation Jobs (NOW HIRING)

Integrate with large language models (LLMs) and generative AI (GenAI) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. * Implement MCP client and server ...

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. . Build and optimize semantic retrieval pipelines, vector search ...

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. . Build and optimize semantic retrieval pipelines, vector search ...

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

AI/ML Engineer

Burbank, CA · On-site

$111K - $153K/yr

Build and deploy RAG (Retrieval-Augmented Generation) pipelines * Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications * Develop and orchestrate agentic AI workflows with ...

AI/ML Engineer

Minneapolis, MN · Remote

$106K - $131K/yr

Familiarity with transformers, LLMs, and Retrieval-Augmented Generation (RAG) pipelines using vector databases. 6. Automation Development: Creating AI-powered automation solutions, including Einstein ...

This role focuses on building scalable systems leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI workflows . The ideal candidate will bring deep expertise ...

Lead AI Engineer

New York, NY · On-site

$170K/yr

This role designs and implements scalable artificial intelligence systems leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) frameworks, AI agents, model orchestration ...

Senior Machine Learning Engineer

OR · On-site +1

$205K - $270K/yr

Architect and scale LLM and retrieval-augmented generation pipelines that ground models in enterprise data. This track focuses on building high-performance ML systems that process complex data ...

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Internship Retrieval Augmented Generation information

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 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 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.

More about Internship Retrieval Augmented Generation jobs
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What are the most commonly searched types of Retrieval Augmented Generation jobs? The most popular types of Retrieval Augmented Generation jobs are:
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What job categories do people searching Internship Retrieval Augmented Generation jobs look for? The top searched job categories for Internship Retrieval Augmented Generation jobs are:
Infographic showing various Internship Retrieval Augmented Generation job openings in the United States as of July 2026, with employment types broken down into 90% Full Time, 8% Part Time, and 2% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution.
Senior GenAl Engineer - Google ADK + Agentic AI

Senior GenAl Engineer - Google ADK + Agentic AI

Compunnel

Charlotte, NC • On-site

$54 - $69.50/hr

Contractor

Posted 6 days ago


Job description

Job Summary
We are seeking a Senior Generative AI Engineer to design, develop, and deploy enterprise-scale Agentic AI and Generative AI solutions. This role is responsible for building production-ready AI applications using Google Agent Development Kit (ADK), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), LangChain, and LangGraph while driving AI platform strategy, engineering standards, and operational excellence. The ideal candidate will have strong software engineering expertise, experience building AI-enabled enterprise applications, and a deep understanding of modern agentic architectures.
Key Responsibilities
• Design, develop, and deploy production-ready AI agents using Google Agent Development Kit (ADK).
• Build multi-agent AI solutions leveraging Google ADK orchestration, tool ecosystems, and deployment frameworks.
• Design and develop Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic architectures.
• Build production-grade AI workflows using LangChain and LangGraph.
• Develop AI-enabled services and integrate AI capabilities into enterprise applications and business workflows.
• Design secure tool execution patterns supporting service-to-service communication, least privilege access, auditability, and enterprise governance.
• Implement enterprise agent-to-agent communication patterns and Model Context Protocol (MCP) tool integrations where applicable.
• Evaluate AI technologies, orchestration frameworks, and model architectures to address complex business requirements.
• Troubleshoot, optimize, and resolve issues across AI models, orchestration frameworks, and production services.
• Develop AI lifecycle capabilities including evaluation frameworks, quality monitoring, model performance tracking, and model drift detection.
• Design, code, test, debug, document, and deploy AI services across development, testing, and production environments.
• Contribute to enterprise AI platform strategy, engineering standards, and operational readiness initiatives.
• Collaborate with architects, engineers, product teams, and business stakeholders to deliver scalable AI solutions.
• Mentor engineers, provide technical leadership, and serve as an escalation point for complex technical challenges.
• Ensure AI solutions comply with organizational security, governance, compliance, and risk management standards.
Required Qualifications
• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field, or equivalent practical experience.
• Strong hands-on experience developing enterprise applications using Python and/or Java.
• Experience developing AI agents using Google Agent Development Kit (ADK).
• Strong understanding of Large Language Models (LLMs), transformer architectures, and conversational AI.
• Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
• Hands-on experience with LangChain and LangGraph frameworks.
• Experience building and deploying production-grade Agentic AI applications.
• Experience implementing Model Context Protocol (MCP) integrations and enterprise AI orchestration patterns.
• Experience with MLOps practices, AI model evaluation, quality monitoring, and model lifecycle management.
• Experience building and managing vector databases for semantic search and knowledge retrieval.
• Experience implementing vector search, embeddings, and enterprise retrieval architectures.
• Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Experience with containerized application deployment and cloud-native architectures.
• Experience implementing CI/CD pipelines and automated software deployment processes.
• Strong analytical, debugging, troubleshooting, and problem-solving skills.
• Excellent verbal and written communication skills with the ability to explain complex AI concepts to technical and business stakeholders.
Preferred Qualifications
• Experience implementing human-in-the-loop workflows, policy guardrails, and AI safety controls for agentic systems.
• Experience with event streaming and messaging technologies such as Apache Kafka.
• Experience with Test-Driven Development (TDD), Behavior-Driven Development (BDD), and modern software engineering practices.
• Experience working in financial services or other regulated industries.
• Experience designing enterprise AI governance, monitoring, and operational frameworks.
• Experience leading AI engineering teams and mentoring software engineers.

Compunnel logo

About Compunnel

Sourced by ZipRecruiter

Compunnel is a well-known company located in Plainsboro, NJ, US, recognized in the industry of IT Services and Solutions. Established in 1989, Compunnel offers a suite of services that help businesses integrate technology efficiently into their operations, a recognizable name in the IT solutions sphere for over three decades. The company’s service portfolio includes Digital Transformation, Business Intelligence, Cloud Services, Cybersecurity, and Application Modern Services, among others. Guided by its mission "to innovate with industry-leading digital solutions and disruptive tech strategies for unimagining business growth," the company underlines its commitment to offering out-of-the-box solutions to its clients. Remarkable achievements of the company include serving more than 30 Fortune 500 companies and providing job opportunities for over 50,000 individuals.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

1994

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