Generative AI Architect

### Generative AI Architect

C2CContractW2 Los Angeles, CA (Remote) Visa: US CitizenGreen CardGC-EADH1BH4-EADTNEAD Job Summary: We are seeking an experienced Generative AI Architect to define and drive the organization's enterprise Generative AI strategy and architecture. The role will focus on designing scalable RAG platforms, multi-agent AI systems, cost-efficient LLM inference infrastructure, and enterprise AI governance frameworks. The ideal candidate will have strong experience in Generative AI, LLM architecture, RAG, vector databases, model serving, cloud AI platforms, and enterprise AI governance, along with the ability to provide technical leadership across AI initiatives. Responsibilities Define the client's multi-year Generative AI blueprint, including technology strategy, architecture roadmap, and platform capabilities. Develop model selection strategies for open-source and proprietary models based on performance, cost, scalability, security, and business requirements. Establish governance standards for GenAI frameworks, models, development practices, and enterprise adoption. Design enterprise-grade RAG architectures using high-throughput vector databases such as Pinecone, Milvus, and pgvector, integrating enterprise data sources including video telemetry, content metadata libraries, and customer data platforms. Architect multi-agent orchestration systems using LangGraph, AutoGen, and Semantic Kernel for complex, multi-step workflows. Define scalable architecture patterns for LLM applications, retrieval systems, agents, tools, and AI workflows. Design cost-efficient and low-latency LLM inference pipelines using AWS Bedrock, Azure OpenAI, and Google Cloud Vertex AI. Define scalable model deployment and inference strategies, including GPU utilization and resource optimization. Implement model optimization techniques including quantization, caching layers, token usage optimization, efficient inference, and workload optimization.