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# Gen AI Architect

- **Company:** Tekshapers Inc
- **Location:** Raritan, NJ, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Python (Programming Language), Google Cloud, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Git, Build Management, Kubernetes, Low Latency, Virtual Agents, Restful APIs, GPT, Docker, Microservices
- **Published:** June 30, 2026
- **Apply:** https://www.dice.com/job-detail/a53b7add-902f-44d6-8ee1-2459d42ae4b2

## About the Role

* Hands-on Gen AI Architect, hybrid work 3-4 days in Raritan, NJ.
 * Must have implemented Gen AI solutions in production, not just POCs.

## Description

* Design, architect, and implement scalable enterprise Generative AI solutions.
 * Build and deploy production-grade Gen AI applications using modern LLM frameworks and cloud technologies.
 * Develop and showcase innovative Gen AI Proofs of Concept (POCs) that address business challenges.
 * Design and implement Agentic AI systems, including autonomous workflows, planning, reasoning, memory, and tool orchestration.
 * Develop robust Python-based AI applications and services with production-quality code.
 * Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and enterprise data sources.
 * Collaborate with business stakeholders, product teams, and engineering teams to translate requirements into AI solutions.
 * Evaluate foundation models and recommend the appropriate architecture based on use cases.
 * Optimize AI solutions for scalability, security, latency, and cost.
 * Mentor engineering teams on Gen AI best practices, architecture patterns, and implementation strategies.

Required Technical Skills

 * Python
 * Large Language Models (OpenAI, Anthropic, Llama, Gemini, etc.)
 * LangChain, LangGraph, LlamaIndex, or similar orchestration frameworks
 * Agentic AI frameworks and autonomous AI systems
 * Retrieval-Augmented Generation (RAG)
 * Vector databases (Pinecone, Weaviate, Chroma, Milvus, FAISS, etc.)
 * Prompt Engineering
 * AI orchestration and workflow automation
 * REST APIs and microservices
 * Git, CI/CD, Docker, Kubernetes
 * Cloud platforms (AWS, Azure, or Google Cloud)


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