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Engagement Architect (Agentic AI / RAG)

Lorven Technologies

 

New York, NY, USA

Posted On: 30+ days ago
Experience: 12+ years
Availability: Onsite
Openings: 1
Category: Engagement Architect
Tenure: No Preference/Any
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Description

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

Education

Any Graduate

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