Application Senior GenAI Architect
AIT Global, Inc.
Jersey City, NJ, United States
5 days ago
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Role details
Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$156,000.0 - $162,240.0
Working hours
Regular working hours
Job source
Tech stack
.NET Framework
Application Programming Interfaces (APIs)
Artificial Intelligence
Business Analytics Applications
Data Analysis
Microsoft Azure
Cloud Computing
Databases
Data Architecture
Information Engineering
Data Infrastructure
Python (Programming Language)
+14 more
Software Deployment
SQL Databases
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
Must-Have Skills:
- 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
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