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Proficient in collaborating with cross‑functional teams to translate business requirements into effective technical solutions. #J-18808-Ljbffr Responsibilities Architect and maintain scalable, secure, and low-latency data pipelines and systems to support agentic AI applications Build and optimize data architectures to support AI/ML/OR (Operations Research) model training, evaluation and deployment Integrate with LLM orchestration frameworks (e.g., LangChain, Semantic Kernel) and support modular data access by multiple agentic processes Monitor and troubleshoot data workflows, ensuring timely and accurate delivery of data to end users Collaborate with data scientists, project managers and supply chain stakeholders to understand data needs and translate business requirements into technical solutions Requirements Degree in Computer Science, Information Technology, Engineering or related field Significant hands‑on experience in AI agent and AI system development Solid understanding of LLMs, autonomous agents, retrieval‑augmented generation (RAG), and memory architectures Extensive hands‑on expertise with the concept and design of data pipelines utilizing different cloud tools such as SnowFlake, Azure, AWS Familiarity with co‑solution development environment such as in Scala, Java or Python Creation of reports and visualization using Power BI, Power App, Power Automate or a similar BI tool Previous experience in: Background in OR, ML model deployment Knowledge of core business processes (Supply Chain, Operations) obtained by directly working in these functions Core Competencies Demonstrates expertise in architecting and maintaining scalable data pipelines and systems for AI applications, with a strong focus on integrating LLM orchestration frameworks and optimizing data architectures for AI/ML model deployment.
