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# GenAI Architect (Onsite)

- **Company:** Hexaware Technologies
- **Location:** Mount Laurel Township, NJ, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Microsoft Azure, Cloud Engineering, Python (Programming Language), Performance Tuning, Software Architecture, Tensorflow, Azure Machine Learning, Pinecone, Pytorch, LangChain, Retrieval-Augmented Generation, Transfer Learning, Large Language Models, Prompt Engineering, Generative AI, Event Driven Architecture, Microsoft Copilot Studio, Containerization, AI Platforms, Kubernetes, HuggingFace, Transformer Architectures, Weaviate, Machine Learning Operations, FAISS, Claude, Api Design, GPT, Docker, Microservices
- **Published:** September 30, 2026
- **Apply:** https://www.dice.com/job-detail/d4bde818-51dd-476e-a513-5dff0ca7c009

## About the Role

* 8+ years of experience in software architecture with 3+ years focused on AI/ML systems
 * Hands-on experience with LLMs, transformers, fine-tuning techniques (LoRA, PEFT), and prompt engineering.
 * Proficient in Python, with libraries/frameworks such as Hugging Face Transformers, LangChain, OpenAI API, PyTorch, TensorFlow.
 * Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) and RAG pipelines.
 * Strong understanding of cloud-native AI architectures (Azure & DBX), containerization (Docker/Kubernetes), and API integration.
 * Deep understanding of LLM architectures, transformer models, and generative AI patterns
 * Experience with MLOps tools and practices (Azure ML, Docker, Kubernetes)
 * Proficiency in Python and familiarity with AI/ML frameworks (PyTorch, TensorFlow, Hugging Face)
 * Experience with Azure AI Foundry, LangChain, LangGraph, and Copilot Studio
 * Strong technical leadership and mentoring capabilities
 * Experience with microservices architecture, API design, and event-driven systems

## Description

* Lead the design and development of scalable GenAI solutions leveraging LLMs, diffusion models, and multimodal architectures.
 * Architect end-to-end pipelines involving prompt engineering, vector databases, retrieval-augmented generation (RAG), and LLM fine-tuning.
 * Select and integrate foundational models (e.g., GPT, Claude, LLaMA, Mistral) based on business needs and technical constraints.
 * Lead architectural reviews and provide technical guidance to development teams
 * Design integration patterns between AI services and existing enterprise systems
 * Create technical roadmaps aligned with business objectives and AI strategy
 * Assess technical feasibility of AI use cases and provide effort estimations