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
Little Neck, NY · 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
Little Neck, NY · 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
Queens, NY · 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
Queens, NY · 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
Garfield, 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
Garfield, 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
Alpine, 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
Alpine, 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
Little Falls, 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
Little Falls, 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
Bronx, NY · 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
Bronx, NY · 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
Maspeth, NY · 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
Maspeth, NY · 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 ...
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
Elizabethport, 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
Elizabethport, 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 ...
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
Staten Island, NY · 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
Staten Island, NY · 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 ...
Retrieval Augmented Generation information
What is a retrieval augmented generation?
A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.
What does a retrieval augmented generation engineer do?
A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.
What skills and qualifications are needed for retrieval augmented generation?
To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.
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Full-time
Posted 6 days ago
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).