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 ...
New
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 ...
New
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 ...
AI Programmer Analyst
Englewood Cliffs, NJ · On-site
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 ...
AI Programmer Analyst
Englewood Cliffs, NJ · On-site
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 ...
AI Programmer Analyst
Leonia, NJ · On-site
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 ...
AI Programmer Analyst
Leonia, NJ · On-site
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 ...
AI Programmer Analyst
Montclair, NJ · On-site
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 ...
AI Programmer Analyst
Montclair, NJ · On-site
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 ...
New
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 ...
New
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 ...
AI Programmer Analyst
Hackensack, NJ · On-site
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 ...
AI Programmer Analyst
Hackensack, NJ · On-site
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 ...
New
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 ...
New
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 ...
New
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 ...
New
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 ...
AI Programmer Analyst
West Paterson, NJ · On-site
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 ...
AI Programmer Analyst
West Paterson, NJ · On-site
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 ...
AI Programmer Analyst
Dumont, NJ · On-site
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 ...
AI Programmer Analyst
Dumont, NJ · On-site
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 ...
AI Programmer Analyst
Haworth, NJ · On-site
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 ...
AI Programmer Analyst
Haworth, NJ · On-site
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 ...
Summer Retrieval Augmented Generation information
What are the key skills and qualifications needed to thrive as a retrieval augmented generation (RAG) engineer, and why are they important?
To thrive as a Retrieval Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and information retrieval, typically supported by a degree in computer science or a related field. Proficiency with frameworks like PyTorch or TensorFlow, experience with vector databases (e.g., FAISS, Pinecone), and familiarity with LLM APIs are commonly required. Creative problem-solving, strong communication, and the ability to collaborate across multidisciplinary teams are essential soft skills. These competencies ensure effective development, deployment, and optimization of advanced AI systems that integrate retrieval and generative capabilities.
What is a summer retrieval augmented generation role?
A Summer Retrieval Augmented Generation (RAG) role typically refers to a summer position focused on developing or improving retrieval-augmented generation systems, which are AI models that combine information retrieval with generative capabilities. In this role, you might work on integrating search algorithms with large language models, enabling systems to fetch relevant information from external sources and generate accurate, context-aware responses. These positions are often found in research labs, tech companies, or startups working on advanced AI applications, and are ideal for students or early-career professionals interested in machine learning, natural language processing, and AI research.
What are some common challenges faced when working on retrieval-augmented generation (RAG) projects during a summer internship?
During a summer internship focused on Retrieval-Augmented Generation (RAG), interns often encounter challenges such as integrating retrieval systems with generative models, managing large-scale datasets, and optimizing latency for real-time responses. Collaboration with cross-functional teams—including data engineers, research scientists, and product managers—is essential for aligning project goals and troubleshooting implementation issues. Additionally, interns may need to balance exploratory research with delivering usable prototypes within tight timeframes, which helps develop both technical and project management skills.
What cities are hiring for Summer Retrieval Augmented Generation jobs?
Cities with the most Summer Retrieval Augmented Generation job openings:
What are the most commonly searched types of Retrieval Augmented Generation jobs?
The most popular types of Retrieval Augmented Generation jobs are:
What states have the most Summer Retrieval Augmented Generation jobs?
States with the most job openings for Summer Retrieval Augmented Generation jobs include:
Full-time
Posted 2 days ago
New
Job description
Job Summary
We are seeking an experienced AI Programmer Analyst to design, develop, and implement enterprise AI solutions that solve complex business challenges and improve operational efficiency. 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 platforms. This role involves collaborating with business and technology teams to deliver scalable, secure, and responsible AI solutions from concept through production deployment.
Roles and Responsibilities- Partner with business and technology stakeholders to identify, evaluate, and implement AI-driven solutions.
- Design, prototype, develop, test, deploy, and maintain enterprise AI applications and intelligent automation solutions.
- Evaluate and select appropriate AI models, frameworks, and architectures based on business and technical requirements.
- Develop and optimize prompts, AI agents, workflows, orchestration pipelines, and retrieval strategies to improve solution accuracy and effectiveness.
- Integrate AI solutions with enterprise applications, APIs, databases, and business processes.
- Build scalable AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent-based architectures.
- Design AI-powered monitoring pipelines that analyze application, server, and database logs to predict system anomalies, recommend real-time resolutions, and automate root-cause analysis.
- Monitor AI model performance, reliability, accuracy, and adoption while continuously improving deployed solutions.
- Ensure AI solutions comply with security, governance, privacy, and Responsible AI standards.
- Create technical documentation, architecture diagrams, implementation guides, and operational runbooks.
- Participate in CI/CD processes, source control, testing, and DevOps practices for AI application delivery.
- Research and recommend emerging AI technologies, frameworks, and best practices.
- 2–10 years of experience in software development, AI application development, or machine learning engineering.
- Strong experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and AI orchestration frameworks.
- Hands-on experience with enterprise AI platforms such as Azure AI, Microsoft Copilot Studio, Gemini Enterprise, or similar AI services.
- Strong Python programming skills with AI/ML libraries and frameworks.
- Experience integrating AI solutions with enterprise applications, REST APIs, databases, and cloud platforms.
- Strong SQL and data analysis skills.
- Experience with cloud-based AI services and enterprise AI platforms.
- Solid understanding of AI/ML concepts, model evaluation techniques, model limitations, and Responsible AI practices.
- Experience with Git, version control, DevOps, and CI/CD pipelines.
- Strong analytical, problem-solving, communication, and documentation skills.
- Experience implementing AIOps solutions for predictive log analysis, automated incident remediation, and root-cause analysis.
- Experience with monitoring and observability platforms.
- Familiarity with MLOps practices, model deployment, monitoring, and lifecycle management.
- Experience developing scalable AI applications in cloud environments.
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field (or equivalent experience).