Generative AI Architect

Title: Generative AI Architect

Location: Plano,TX

Experience: 8-15 yrs

C2C or W2 or Fulltime

We are looking for an experienced and hands-on Generative AI (GenAI) Architect to design and implement enterprise-scale AI solutions. The ideal candidate will have strong experience with LLMs, Agentic AI, RAG, MLOps/LLMOps, cloud architecture, and enterprise production deployments.

The candidate must have proven experience taking GenAI solutions from prototype/POC to scalable enterprise production environments.

Key Responsibilities

• Architect and implement end-to-end Generative AI and Agentic AI solutions.
• Design enterprise-grade solutions using LLMs, RAG, multi-agent workflows, and vector databases.
• Build scalable AI architectures on Microsoft Azure or Google Cloud Platform (Google Cloud Platform).
• Lead GenAI solutions from POC/prototype through production deployment.
• Integrate GenAI solutions with enterprise applications, APIs, data platforms, and cloud services.
• Establish MLOps/LLMOps practices for deployment, monitoring, and lifecycle management.
• Design solutions considering enterprise security, scalability, governance, reliability, and integration requirements.

Must-Have Skills

• 8 10+ years of experience in Software Engineering, Data Science, Machine Learning, or AI.
• 3+ years of experience as a Solution Architect/System Architect.
• Strong enterprise-level experience architecting and deploying GenAI solutions in large-scale production environments.
• Hands-on experience with Generative AI, LLMs, RAG, and Agentic AI/Multi-Agent architectures.
• Strong programming experience in Python.
• Experience with LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks.
• Strong cloud architecture experience with Microsoft Azure or Google Cloud Platform.
• Hands-on experience with vector databases such as Pinecone, Milvus, Qdrant, or PGVector.
• Strong understanding of MLOps/LLMOps, model deployment, monitoring, and productionization.
• Experience with SQL, PySpark, distributed computing, and API design.
• Experience with PyTorch or TensorFlow.

Preferred Skills

• Experience designing and implementing multi-agent AI ecosystems.
• Strong knowledge of enterprise AI security, governance, scalability, and integration patterns.
• Experience integrating GenAI/LLM solutions with existing enterprise applications and data platforms.