Staff Data Scientist, SMAI OI

We are seeking a highly motivated Agentic AI Data Scientist to lead the design and deployment of next-generation AI agents that drive end-to-end planning and operational optimization within SMAI (Smart Manufacturing & AI).This role focuses on building goal-driven, multi-step AI systems (“agents”) that can autonomously plan, decide, and execute workflows across manufacturing planning, capacity optimization, and operations intelligence—unlocking cycle time reduction, capacity improvements, and decision automation at scale.Key Responsibilities1. Agentic AI Design & DevelopmentDesign and develop agent-based AI systems capable of:Multi-step reasoning (planning + decision-making + execution)Autonomous orchestration across workflows and platformsBuild multi-agent architectures for complex planning and operations use casesDevelop agents that integrate:Optimization models (OR / mathematical programming)LLM-based reasoning and tool usageEnsure agents align with enterprise data, domain knowledge, and planning constraints2. Planning & Operations Use Case DeliveryApply Agentic AI to key business problems such as:Capacity planning and capital investment optimizationProduction flow optimization and cycle time reductionScenario simulation and decision supportTranslate business requirements into:Structured optimization problemsAI-driven decision workflows3. AI System Integration & DeploymentIntegrate agents into:Existing SMAI platforms and toolsData pipelines and enterprise systemsDevelop reusable frameworks for:Agent orchestrationKnowledge retrieval (RAG / knowledge graph)Drive deployment strategy (embedded vs standalone agents depending on use case)4. Cross-Functional CollaborationPartner with:Planning, Operations, and Manufacturing teamsData Engineering, MLOps, and Platform teamsTranslate domain knowledge into AI logic and workflowsCommunicate technical solutions to business stakeholdersRequired SkillsetsCore AI / Software EngineeringStrong programming skills in Python (preferred), plus familiarity with modern AI frameworksExperience with LLMs / GenAI ecosystems (e.g., agent frameworks, tool-use, orchestration)Solid understanding of:Prompt engineeringRetrieval-Augmented Generation (RAG)Multi-agent systemsOptimization & Decision Science (Critical)Strong background in Operations Research / Optimization, including:Linear / Mixed Integer ProgrammingHeuristics / metaheuristicsSimulation modelsExperience translating real-world planning problems into mathematical modelsAgentic AI & System DesignUnderstanding of agentic AI principles:Goal-based and utility-based agentsPlanning + reasoning + execution loopsExperience designing:Autonomous workflowsMulti-step decision systemsTool-using AI agentsData & Systems IntegrationExperience working with:Structured and unstructured dataAPIs and enterprise systems integrationFamiliarity with:Data pipelines (e.g., Spark, SQL)MLOps / deployment pipelinesBusiness & Domain Skills (Preferred)Experience in manufacturing, supply chain, or planning domainsStrong problem-solving skills with ability to:Connect AI solutions to business valueQuantify impact (capacity, cost, cycle time)Minimum QualificationsBachelor’s or Master’s degree in:Computer Science, Data Science, Industrial Engineering, Operations Research, or related field3–5+ years of experience in:AI/ML engineering, orOptimization / decision science, orAdvanced analytics in operations/planningProven experience building production-grade AI or optimization solutionsPreferred QualificationsPhD in AI, Machine Learning, or Operations ResearchExperience with:Agent frameworks (LangChain, AutoGen, CrewAI, etc.)Reinforcement learning or adaptive systemsKnowledge graphs and domain-specific AI tuningExperience in semiconductor or advanced manufacturing environments