GenAI Solutions Architect

Role: GenAI Solutions Architect (Onsite)


Location: Mount Laurel, NJ


Experience: 12-15 years

Job 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

Technical skills:

• • 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