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Assistant 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 a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Key Responsibilities:

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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Assistant Retrieval Augmented Generation information

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

AspectAssistant Retrieval Augmented GenerationData Analyst
Required CredentialsKnowledge of AI, NLP, and retrieval systemsBachelor's in Statistics, Data Science, or related fields
Work EnvironmentTech companies, AI development teamsBusiness, finance, healthcare sectors
Industry UsageAI, machine learning, natural language processingData analysis, reporting, decision support

Assistant Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, often requiring expertise in AI and NLP. Data Analysts interpret data to generate insights, primarily using statistical tools. While both roles involve working with data, Assistant Retrieval Augmented Generation is centered on AI model development, whereas Data Analysts focus on data interpretation and reporting.

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 Assistant Retrieval Augmented Generation jobs in New York? For Assistant Retrieval Augmented Generation jobs in New York, the most frequently searched job titles are:
What job categories do people searching Assistant Retrieval Augmented Generation jobs in New York look for? The top searched job categories for Assistant Retrieval Augmented Generation jobs in New York are:
What cities in New York are hiring for Assistant Retrieval Augmented Generation jobs? Cities in New York with the most Assistant Retrieval Augmented Generation job openings:

Engagement Architect (Agentic AI/RAG)

Lorven Technologies

Jersey City, NJ • On-site

Full-time

Posted 27 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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