AWS Senior Solution Architect in Charlotte, NC(Onsite)-Contract

Role: AWS Senior Solution Architect Location : Charlotte, NC Contract Job Description: Role Summary We are looking for a highly experienced Agentic AI Architect to lead the design and implementation of enterprise-scale agentic AI solutions. This role will be responsible for defining architecture, guiding development teams, and ensuring scalable, secure, and high-performing AI systems that leverage LLMs, multi-agent frameworks, and enterprise integrations. The ideal candidate combines deep technical expertise in AI/ML with strong architectural design skills and experience delivering complex, production-grade AI solutions. Key Responsibilities Define end-to-end architecture for agentic AI solutions, including multi-agent systems, orchestration layers, and integrations Design and implement scalable agent frameworks using technologies such as LangChain, Semantic Kernel, AutoGen, CrewAI, etc. Lead development of LLM-driven systems (Azure OpenAI, OpenAI, Anthropic, etc.) with robust prompting strategies Architect RAG pipelines, memory systems, and tool integration layers Establish best practices for AI governance, security, and Responsible AI Design integration strategies with enterprise systems (CRM, ERP, APIs, data platforms) Provide technical leadership, mentorship, and code quality oversight to development teams Collaborate with business stakeholders to translate requirements into technical solutions Ensure performance, scalability, reliability, and cost optimization of AI systems Drive innovation by evaluating emerging AI technologies and frameworks Required Skills & Experience 10+ years of experience in software engineering, AI/ML, or solution architecture Strong expertise in Python and modern backend architectures Hands-on experience with LLM ecosystems and agent frameworks Proven experience designing multi-agent systems and distributed architectures Deep understanding of: - Prompt engineering and LLM optimization - Embeddings and vector databases (FAISS, Pinecone, Azure AI Search, etc.) - Retrieval-Augmented Generation (RAG) Experience with cloud platforms (Azure preferred, AWS/Google Cloud Platform acceptable) Strong knowledge of API design, microservices, and event-driven architecture Familiarity with security, authentication (OAuth, SSO), and data governance Experience leading technical teams and driving architecture decisions Good to Have Experience with Model Context Protocol (MCP) or similar integration standards Exposure to enterprise AI transformation programs Knowledge of MLOps / LLMOps frameworks Experience with frontend or conversational UI frameworks Certifications (Azure AI Engineer, Solutions Architect, etc.)