Role: AWS AI Bedrock Developer Location: Charlotte, NC (100% Onsite) Long Term Contract – W2 / C2C Client is seeking a highly skilled AI Agent Developer to design, build, and deploy intelligent autonomous agents using cutting-edge frameworks and generative AI platforms. This role requires deep expertise in prompt engineering, agent orchestration, and working with AWS-native services, particularly Amazon Bedrock. Core Competencies: • AWS Cloud Computing • Artificial Intelligence / Generative AI Key Responsibilities: • Autonomous Agent Development: • Design, develop, and deploy multi-step, multi-tool AI agents capable of reasoning, decision-making, and task execution. • Leverage frameworks like Lang-Chain, Semantic Kernel, or custom-built orchestration layers to power agent behavior. • Prompt Engineering: • Craft, refine, and optimize advanced prompts to improve LLM accuracy, reliability, and contextual performance. • Develop and manage prompt chains, system prompts, and dynamic context strategies to enable adaptive agent responses. • Continuously test and iterate prompts based on performance metrics and user feedback. • Amazon Bedrock Development: • Implement generative AI solutions using Amazon Bedrock with models from providers such as Anthropic (Claude), Cohere, Stability AI, and Amazon Titan. • Utilize Bedrock capabilities including Guardrails, Knowledge Bases, and model customization to ensure safe and scalable AI deployments. Essential Skills: • Overall IT Experience: 9-12+ Years • Proven experience developing autonomous AI agents using LangChain, Semantic Kernel, or similar frameworks • Expertise in prompt engineering, including design, chaining, and iterative refinement for large language models (LLMs) • Hands-on experience with Amazon Bedrock (model integration, guardrails, knowledge bases) • Proficiency in Python, API integration, and vector databases such as FAISS or Pinecone • Strong understanding of LLM behavior, Retrieval-Augmented Generation (RAG) architecture, and AWS deployment best practices Desirable Skills: • Advanced knowledge of AI agent orchestration frameworks • Experience fine-tuning or customizing foundational models • Familiarity with prompt evaluation tools and automated testing for LLMs • Exposure to real-world AI use cases in enterprise-scale environments