What You Will Do: * Partner with Product and business teams to identify high-value AI and Generative AI use cases, then lead the technical solutioning process to build the detailed architecture for how AI will solve the problem * Consider the enterprise picture as part of AI solution design to produce reference architectures and patterns consistent with IT technical vision, data strategy, and responsible-AI standards * Leverage expertise across multiple technical domains as part of the solutioning process (Machine Learning, GenAI/LLMs, Data Engineering, Security, Cloud Infrastructure, Application Integration, etc.) What Will Put You Ahead: * Experience in supporting discrete engineering and manufacturing * Experience designing and deploying agentic AI - conversational and action-oriented AI agent platforms - to solve business problems * Deep understanding of Generative AI and large language model architecture (transformer models, fine-tuning, RAG, embeddings, and prompt/context engineering) * Experience operationalizing AI - LLMOps/MLOps practices for model deployment, evaluation, prompt and version management, monitoring, and drift detection * Experience with vector databases and retrieval systems (e.g., Azure AI Search, pgvector, Pinecone) * Experience with AI orchestration and agent frameworks (LangChain, LlamaIndex, Semantic Kernel, AutoGen, or similar) * Experience with data architecture that supports AI (data lakes, graph/knowledge-graph technology, feature stores, and data pipelines) * Experience with DevOps and MLOps methodologies and tools (CI/CD, GitHub, Azure DevOps) Hourly employees are not eligible for paid time off unless required by law. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply.
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