GenAI Architect

AIT Global, Inc.

New York, NY, United States

8 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Business Analytics Applications Data Analysis Cloud Computing Databases Data Architecture Information Engineering Data Infrastructure Python (Programming Language) Software Deployment SQL Databases

+12 more

Unstructured Data Enterprise Data Management Data Processing Large Language Models Multi-Agent Systems Generative AI Data Analytics Enterprise Integration Virtual Agents GPT Data Pipelines Microservices

Job description

We are looking for a Senior GenAI Architect with strong expertise in Data Engineering, Analytics, Generative AI, and Agentic AI workflows. The candidate will design and build scalable AI-driven solutions that leverage enterprise data, LLMs, RAG, and agent-based architectures., * Design and develop GenAI and Agentic AI applications using Python and modern AI frameworks.

Build scalable data pipelines, data processing, and analytics solutions.
Develop LLM/RAG-based applications integrating enterprise data sources.
Design and implement agentic workflows, AI agents, orchestration, and tool integrations.
Work with structured and unstructured data to support AI and analytics use cases.
Integrate LLMs with APIs, databases, knowledge sources, and enterprise platforms.
Implement evaluation, monitoring, security, and governance for GenAI solutions.
Collaborate with Data Engineers, Data Scientists, Architects, and business stakeholders.
Drive solutions from POC/prototype through production deployment.

Requirements

15+ years of software/data engineering experience
Strong Python
Generative AI / LLM / RAG
Agentic AI / AI Agents / Agent Orchestration
Strong Data Engineering & Analytics
SQL and modern data platforms
Experience with APIs, microservices, and cloud platforms
Experience with LLM frameworks such as LangChain, LangGraph, or similar
Strong understanding of AI architecture, data architecture, and enterprise integration
Excellent communication and stakeholder management skills