Hexion Careers

Role Description Serve as the engineering lead for Agentic AI delivery across Supply Planning and Manufacturing — owning the design, development, and deployment of production-grade AI agent solutions. - Architect and build multi-agent AI systems using Azure AI Agent Service, AutoGen, Semantic Kernel, and/or LangChain/LangGraph — including orchestrator-executor patterns, tool calling, memory management, and agent coordination. - Implement the MCP to surface enterprise data as structured context for AI agents operating in supply chain and manufacturing workflows. - Build and deploy generative AI solutions on Azure AI Foundry — RAG-based knowledge agents, decision support for forecasting and capacity planning, and document intelligence for maintenance work orders and recipes. - Design and deliver AI copilots and topic-based agents using Microsoft Copilot Studio — enabling Supply Planning and Manufacturing teams to access insights and take action directly from Teams and Outlook. - Act as the AI delivery owner for agentic use cases — scoping business problems with stakeholders, defining agent capabilities and tool surfaces, prioritizing the roadmap, and driving adoption. - Apply emerging agentic AI patterns — including ReAct, Plan-and-Execute, reflection, and human-in-the-loop — for supply chain and operational use cases. - Partner with Supply Chain leadership, Demand Planning, Process Engineering, Maintenance Ops, and Plant teams to identify, scope, and deliver AI use cases that influence operational decisions. - Define and maintain AI agent governance — prompt versioning, tool auditing, evaluation frameworks, observability, and safety guardrails for production deployments. - Develop on Azure Databricks — PySpark and SQL against gold/platinum Delta tables, notebooks for transformation and feature work, and orchestration via Workflows. - Build and maintain Power BI reports and semantic models that serve as grounding data for AI agents and executive dashboards across Supply Planning and Manufacturing. - Own Supply Chain AI metrics alignment cadence — keeping priorities, status, and roadblocks visible to Supply Chain and Manufacturing leadership. - Mentor analysts and engineers on agentic AI design patterns, MCP, and AI delivery best practices. Qualifications - Master’s degree in Mathematics, Computer Science, Data Science, Information Systems, Engineering, or a related field with 5+ years of relevant analytics / AI experience, OR - Bachelor’s degree in Chemical, Industrial, Computer Science, or related fields with 8+ years of relevant analytics / AI experience. Requirements - Hands-on experience with the MCP — building or consuming MCP servers/clients; ability to expose enterprise data sources (databases, APIs, SharePoint, ERP) as MCP tools for AI agents. - Hands-on experience with multi-agent system design — designing and implementing multi-agent architectures; orchestrator-executor patterns, tool calling, memory management, and agent coordination using AutoGen, Semantic Kernel, LangChain/LangGraph, or Azure AI Agent Service. - Strong Python engineering skills — building production-grade AI agents and pipelines, including REST API integration, prompt versioning, evaluation frameworks, and observability for LLM-based systems. - Compulsory — must have hands-on experience with two or more of the following: - Azure AI Foundry (RAG pipelines, prompt flows, agent service) - Microsoft Copilot Studio (agents, topics, actions, Power Automate integration) - Microsoft 365 Copilot extensibility (plugins, connectors, Graph APIs) - Microsoft Power BI (DAX, semantic modeling, performance tuning) - Strong proficiency in Databricks (Python, SQL, Delta Lake, PySpark, notebooks). - Strong functional understanding of Supply Planning (S&OP, demand/supply planning, inventory, order management) and/or Manufacturing (plant maintenance, capacity planning, OEE). - Experience with SAP ECC / S/4HANA supply chain and manufacturing modules (MM, PP, SD, PM). - Ability to translate business problems into agentic AI solutions and communicate clearly to technical and executive audiences. - Strong collaboration and stakeholder management skills in cross-functional environments. Preferred Qualifications - Experience deploying AI agents in production — evaluation frameworks, safety guardrails, logging, and human-in-the-loop workflows. - Familiarity with agentic design patterns (ReAct, Plan-and-Execute, reflection, structured tool outputs). - Familiarity with knowledge graphs or graph databases (e.g., Neo4j) for agent reasoning and grounding. - Strong Power BI experience — semantic modeling, performance optimization, executive dashboard design. - Experience in chemicals, manufacturing, or process industries. - Experience with Palantir Foundry (pipelines, ontology, Workshop, AIP). - Exposure to MLOps on Azure (Azure ML, MLflow, Databricks Asset Bundles, CI/CD for analytics). - Experience designing operational KPI frameworks (MAPE, OTIF, service level, OEE, downtime). - Experience with containerization (Docker), version control (Git), and modern software engineering practices. Other We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

Role Description The Principal Manufacturing & Semantic Architect is a critical leadership role responsible for defining and governing the canonical data and semantic model that underpins Hexion's industrial digital platform. This role will establish how manufacturing assets, processes, materials, and data are consistently represented across: - Plant systems (OT) - Enterprise systems (IT) - Cloud platforms - AI/ML models - Customer-facing applications The successful candidate will bring deep expertise in industrial standards (ISA-95 / ISA-88) and translate complex manufacturing environments into scalable, structured data models that enable interoperability, analytics, and AI. Key Responsibilities - Define and Govern the Canonical Manufacturing Data Model - Develop and maintain a standardized semantic model aligned with: - ISA-95 (enterprise-control integration) - ISA-88 (batch/process control) - Emerging industry standards (e.g., CFIHOS where applicable) - Define core entities including: - Assets, equipment hierarchies, and locations - Materials, batches, and process segments - Operational states, events, and relationships - Ensure consistent representation of manufacturing data across all systems. - Establish Semantic Standards and Data Contracts - Define and enforce: - Data schemas - API and event contracts - Naming conventions and units of measure - Partner with engineering teams to ensure adherence across: - Edge systems - Cloud services - Integration layers - Prevent semantic drift across teams, platforms, and external partners. - Define Semantic Meaning and Canonical Structure of AI Features - Define the semantic meaning and canonical structure of features used in predictive and optimization models. - Establish what each feature represents in the context of manufacturing processes and operational data. - Define feature-level semantic definitions grounded in manufacturing domain knowledge. - Ensure alignment between the meaning of training data and real-time operational data at the edge. - Collaborate with data science teams to ensure models reflect real-world process behavior. - Provide Semantic Translation Between OT, IT, and Digital Platforms - Serve as the authority on semantic and data model translation between: - Plant floor systems (PLC, DCS, SCADA, historians) - MES and ERP systems - Cloud-based data and application platforms - Ensure data models are both technically robust and operationally practical. - Support Platform Productization and External Solutions - Design semantic models that ensure the data model scales across tenants, including: - Multiple manufacturing sites - Multi-tenant environments - External customer-facing products - Ensure extensibility and long-term maintainability of the data model. - Lead Governance and Continuous Evolution - Establish versioning and lifecycle management for: - Data models - Schemas - Semantic definitions - Facilitate cross-functional alignment across engineering, operations, and data teams. - Serve as the final authority on semantic architecture decisions. - Collaborate Across Teams - Partner with: - Principal Edge & OT Architect (semantic model enforcement at the edge and OT data normalization) - Principal Industrial AI Data Architect (feature semantics and data pipeline alignment) - Platform Engineering (implementation of semantic standards in cloud services) - Plant Operations and Process Engineering teams (domain validation and real-world grounding) - Ensure consistent execution across domains. Qualifications - Bachelor's degree in Engineering, Computer Science, Industrial Engineering, or related field (Master's preferred) - 10+ years of experience in manufacturing systems, industrial automation, or process engineering - 10+ years of experience in data modeling or system architecture in industrial environments - Demonstrated expertise in ISA-95 and ISA-88 standards and manufacturing data structures and hierarchies - Strong understanding of OT systems (PLC, DCS, SCADA, historians) - Strong understanding of MES and ERP integration patterns - Experience with relational and/or graph-based data modeling Preferred Qualifications - Experience with ISA or similar industry data standards - Industrial IoT platforms or edge-to-cloud architectures - AI/ML applications in manufacturing environments - Cloud platforms (AWS preferred) - Familiarity with time-series data and event-driven architectures - Data governance frameworks Leadership Expectations - Operate as a thought leader in industrial data and semantic architecture - Influence without direct authority across multiple teams and partners - Drive standards adoption across internal and external stakeholders - Balance long-term architectural vision with near-term delivery needs Work Environment & Travel - Travel to manufacturing sites and partner locations as needed (~10–25%). Other We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

Role Description Partner with Commercial, Supply Chain, Finance, Procurement, and Ops to identify and prioritize high-impact AI/automation use cases. Own end-to-end delivery of AI/ML solutions integrated with ERP (automation, predictive analytics, and LLM assistants in workflows). Job Responsibilities - Define requirements (PRDs, user stories, acceptance criteria) and align business users with delivery teams (DS/Eng/IT). - Enable ERP-native AI and third-party integrations (e.g., invoice automation, forecasting, procurement, inventory, order mgmt.). - Identify automation-ready processes, map/redesign workflows with process owners, and coordinate RPA implementation. - Drive adoption: training, SOP updates, usage metrics, and continuous improvement based on feedback. - Own the backlog and roadmap; manage priorities and communicate progress and outcomes. - Operate within AI governance, data, and compliance standards; manage risks and escalate blockers early. - Support vendor/tool evaluations for AI and automation platforms with IT and leadership. - Create enablement materials and run working sessions to help teams adopt AI-assisted workflows. Qualifications - 5–7 years in product, ERP, process automation, or digital transformation with hands-on delivery ownership. - SAP ECC/S4 experience; understanding of modules (MM/SD/FI/PP) and ability to translate processes into requirements. - RPA experience (UiPath, Power Automate, or similar); able to spot and size automation opportunities. - Working knowledge of AI/ML and GenAI (RAG, copilots/agents, LLM integration) to partner with DS/Eng teams. - Strong product execution: specs, backlog ownership, and agile/hybrid delivery. - Proven adoption focus—driving trust, usage, and measurable business outcomes. - Comfortable with integrations (APIs, middleware) to connect AI solutions with ERP and adjacent systems. - Clear communicator with business stakeholders; can translate technical concepts without heavy jargon. Preferred Qualifications - Azure data/AI (Databricks, Azure OpenAI, Data Factory). - Palantir Foundry and/or supply chain/procurement analytics tools. - CRM (Salesforce/Dynamics), ideally in B2B manufacturing/chemicals. Requirements - Equal Opportunity, Affirmative Action employer. - All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. - Candidates are required to submit an application for employment through our career site and be at least 18 years of age. - Any offer of employment will be conditioned upon successful completion of a drug test and background investigation. - Authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. - A prior criminal record is not an automatic bar to employment; the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

Role Description The Chemical Regulatory Compliance Consultant serves as the program manager for Hexion’s global chemical reporting activities, with primary responsibility for planning, coordinating, and executing reporting obligations across regions using structured project management methodology. This includes ownership of programs such as PFAS reporting, Extended Producer Responsibility (EPR), and Chemical Data Reporting (CDR), ensuring accurate data collection, validation, and on-time submission while driving cross-functional alignment, managing timelines, and maintaining data integrity within SAP and related systems. As a secondary responsibility, the role contributes to the authoring, maintenance, and continuous improvement of Safety Data Sheets (SDS) and labeling to ensure bench strength within the team. This includes: - Reviewing raw material SDS - Managing raw material data - Supporting substance hazard evaluations and classification - Monitoring chemical composition - Assessing impacts of raw material changes - Supporting dangerous goods classification - Maintaining regulatory data to enable compliance and safe commercialization across global markets Working within a cross-functional environment, the Chemical Regulatory Compliance Consultant partners with manufacturing, commercial, regulatory, and IT teams to execute global reporting programs and ensure consistency in hazard communication and regulatory practices. Qualifications - Bachelor's Degree or equivalent experience - 7+ years experience in chemical regulatory compliance, product stewardship, or EHS - Strong project management capability including managing timelines, dependencies, and cross-functional inputs - Experience with Global Chemical Regulatory Reporting (CDR, EPR, PFAS) - Experience working with regulatory or EHS systems (e.g., SAP EHS or similar platforms) - Hands-on experience authoring and maintaining Safety Data Sheets (SDS) and labels Requirements - Attention to detail with the ability to manage complex regulatory data accurately - Analytical skills to assess regulatory impacts and interpret technical information - Effective communication skills for cross-functional collaboration and training - Ability to drive cross-functional alignment, manage competing priorities, and execute structured project plans using project management tools and methodologies - Strong skill in leveraging AI tools to support regulatory analysis, hazard assessment, and compliance activities, with a willingness to experiment and challenge traditional approaches - Knowledge of chemical regulatory frameworks (GHS, OSHA) - Global chemical reporting data gathering and submission - Working knowledge of project management frameworks and their application to global chemical reporting - Understanding of dangerous goods transportation regulations and classification systems Company Description We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. To be considered for this position candidates are required to submit an application for employment through our career site and be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

Role Description Lead Hexion’s enterprise Agentic AI and automation strategy—architecting and scaling agentic AI capabilities, identifying automation opportunities across all business functions, championing AI fluency and a learning culture, and overseeing the execution and KPI governance of automation initiatives to deliver measurable business value across the organization. Job Responsibilities - Build AI-powered applications that deliver agentic and generative AI capabilities to business users across commercial, supply chain, manufacturing, and R&D functions. - Develop and tune Retrieval-Augmented Generation (RAG) pipelines over unstructured content such as product specs, Safety Data Sheets, standard operating procedures, emails, and meeting transcripts — using parsing (Azure Document Intelligence, Unstructured), chunking, embeddings, hybrid search, and reranking. - Create domain-specific tools and connectors (including Model Context Protocol servers) that expose enterprise systems — ERP, planning, analytics, content management, and custom APIs — as safe, well-documented actions for AI agents to call. - Build user-facing surfaces with Microsoft Copilot Studio, Power Apps, Teams apps, Streamlit, or React — including chat interfaces, approval workflows, and result-review screens. - Implement data validation and guardrails at every tool boundary: schema checks, business-rule validation, content safety, PII handling, and explicit user confirmation for write operations. - Partner with product owners and subject-matter experts to gather requirements, translate workflows into agent execution plans, prototype rapidly, demo, gather feedback, and iterate. - Support deployment and operations of the applications you build: package for production on Azure AI Foundry or Container Apps, add tracing and logging, monitor usage and quality, and respond to production issues. - Apply prompt engineering and evaluation to measure application quality — build test cases, run LLM-as-judge evals, and track regressions over time. - Document use cases, tools, and playbooks so applications remain maintainable and extensible by the team. - Collaborate across globally distributed teams through code reviews, pair programming, and shared technical standards. Qualifications - Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field — or equivalent hands-on experience. - 5+ years of professional software development or data/analytics engineering experience, including recent hands-on work with LLMs or AI-powered applications (professional projects, internships, or substantive personal projects). - Strong proficiency in Python and comfort with TypeScript or JavaScript for front-end work. - Working knowledge of at least one AI/agent framework: LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, or CrewAI. - Practical experience with LLM APIs (Azure OpenAI, Anthropic Claude, OpenAI, or Hugging Face) and structured outputs. - Hands-on RAG experience — document parsing, chunking, embeddings, and hybrid retrieval — with at least one vector database. - Comfort integrating with enterprise APIs such as ERP, BI platforms, SharePoint or Microsoft Graph, Teams, and REST/GraphQL services. - Solid SQL skills and working familiarity with a modern data platform (Databricks, Snowflake, or equivalent). - Self-directed learner who stays current with a fast-moving field, can teach themselves new frameworks with minimal guidance, and ships working software without hand-holding. - Strong problem-solving, communication, and documentation skills; comfortable demoing to business stakeholders and gathering requirements directly from subject-matter experts. - Familiarity with Git, CI/CD, and basic DevOps workflows. Preferred Qualifications - Hands-on experience with Microsoft Copilot Studio, Microsoft 365 Copilot extensibility, or Power Platform (Power Apps, Power Automate). - Experience with Azure AI Foundry agents or Palantir AIP Logic / Workshop applications. - Familiarity with Model Context Protocol (MCP), tool/function calling, and prompt registries. - Experience with LLM observability and evaluation tooling — LangSmith, Langfuse, Arize, or Weights & Biases. - UX sensibility — ability to design clean, low-friction chat and approval interfaces that business users actually adopt. - Exposure to Docker, containerized deployments, and infrastructure-as-code (Terraform or Bicep). - Public portfolio — GitHub projects, technical blog posts, or community contributions — demonstrating curiosity and hands-on experimentation in generative or agentic AI. - Prior experience delivering business applications in process industries, manufacturing, supply chain, or commercial analytics. Other We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

Role Description Lead Hexion’s enterprise Agentic AI and automation strategy—architecting and scaling agentic AI capabilities, identifying automation opportunities across all business functions, championing AI fluency and a learning culture, and overseeing the execution and KPI governance of automation initiatives to deliver measurable business value across the organization. Job Responsibilities - Design and build agentic AI systems using modern frameworks such as Microsoft AutoGen, Semantic Kernel, LangGraph, LangChain, or CrewAI — including single-agent, multi-agent, supervisor, and handoff orchestration patterns. - Develop end-to-end agent logic: planning loops, tool use, structured outputs, short- and long-term memory, state management, and human-in-the-loop checkpoints. - Integrate Large Language Models (Azure OpenAI, Anthropic Claude, open-weight models) into business applications with attention to quality, latency, and cost. - Build Retrieval-Augmented Generation (RAG) pipelines — document parsing, chunking, embeddings, hybrid search, and reranking — against vector stores such as Azure AI Search, Databricks Vector Search, Pinecone, or FAISS. - Develop tools and connectors (including Model Context Protocol servers) that expose enterprise data sources and APIs as safe, well-documented actions for agents to call. - Apply prompt engineering best practices and build evaluation harnesses — golden datasets, LLM-as-judge, deterministic assertions — to measure and regression-test agent behavior. - Contribute to deployment and observability: package agents for production on Azure AI Foundry or Container Apps, add tracing (LangSmith, Langfuse, or OpenTelemetry), and help monitor token spend, latency, and failure modes. - Implement guardrails for content safety, PII handling, and safe-action confirmations before any write operation against enterprise systems. - Collaborate with product owners and subject-matter experts to translate business workflows into agent execution plans; prototype rapidly, demo, and iterate. - Maintain high code quality through Git-based workflows, code reviews, unit and integration testing, and clear technical documentation. Qualifications - Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field — or equivalent hands-on experience. - 5+ years of professional software, AI/ML, or data engineering experience, including recent hands-on work with LLMs or agentic workflows (professional projects, internships, or substantive personal projects). - Strong proficiency in Python (asynchronous programming, typing, FastAPI or similar) and solid software engineering fundamentals — APIs, Git, testing, and version control. - Working knowledge of at least one agent framework: Microsoft AutoGen, Semantic Kernel, LangGraph, LangChain, LlamaIndex, or CrewAI. - Practical experience with LLM APIs (Azure OpenAI, Anthropic Claude, OpenAI, or Hugging Face models) including prompt engineering, function/tool calling, and structured outputs. - Understanding of core agentic concepts: multi-step reasoning, planning, tool use, memory, and multi-agent orchestration. - Familiarity with RAG patterns, vector databases, embeddings, and retrieval evaluation. - Exposure to cloud development on Microsoft Azure (Azure AI Foundry, Azure OpenAI, Azure Functions, Azure AI Search) or equivalent. - Self-directed learner who stays current with a fast-moving field, reads primary sources, and can teach themselves new frameworks with minimal guidance. - Strong problem-solving skills and the ability to work independently while collaborating across globally distributed teams. - Clear written and verbal communication; able to explain technical concepts to non-technical stakeholders. Preferred Qualifications - Hands-on experience with Microsoft Copilot Studio, Microsoft 365 Copilot extensibility, or declarative agent plugins. - Exposure to Palantir AIP, Foundry, or Ontology-driven AI applications. - Experience with Databricks (Mosaic AI, Unity Catalog, MLflow) or Snowflake Cortex. - Familiarity with Model Context Protocol (MCP), tool/function calling, and structured output schemas. - Exposure to LLM observability and evaluation tooling — LangSmith, Langfuse, Arize, or Weights & Biases. - Knowledge of GraphRAG, knowledge graphs, or semantic modeling. - Experience with CI/CD (Azure DevOps or GitHub Actions), Docker, and infrastructure-as-code (Terraform or Bicep). - Public portfolio — GitHub projects, technical blog posts, open-source contributions, or hackathon work — demonstrating curiosity and hands-on learning in generative or agentic AI. - Prior experience delivering AI applications in an enterprise setting, particularly in process industries, manufacturing, supply chain, or commercial analytics. Other We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

Role Description Hexion is seeking a senior, hands-on Azure data engineer to lead the design, implementation, and production support of enterprise data integrations. The role is centered on Azure Data Factory, Azure Logic Apps, and Databricks as well as other adjacent Azure data services to deliver governed, reliable, and maintainable pipelines. You will work closely with architecture, security, and infrastructure teams to apply the right guardrails to enable Hexion’s business objectives. Job Responsibilities - Azure Data Engineering & Integration - Lead the design, development, and implementation of Azure Data Factory pipelines, Azure Logic Apps workflows and related Azure data solutions to meet business requirements. - Collaborate with business, architecture, and technical teams to translate data requirements into Azure integration deliverables. - Develop and enforce best practices for data pipeline development, ETL processes, data quality, governance, and documentation. - Optimize, monitor, and troubleshoot existing pipelines to improve performance, reliability, and maintainability. - Support integrations across Azure services such as Azure SQL Database, Azure Data Lake Storage, Azure Databricks, and Power BI. - Data Platform Enablement (Azure) - Coordinate with platform teams to onboard data workloads into approved Azure environments (subscriptions/resource groups), ensuring required standards (naming, tagging, logging) are met. - Define repeatable environment and deployment patterns for data products (dev/test/prod), including configuration, secrets, and release boundaries for internal teams and vendors. - Ensure prerequisite platform capabilities are available for data delivery (e.g., access to ADLS, Azure SQL, Databricks workspaces), partnering with owners to provision when needed. - Apply governance guardrails for data workloads (policies/controls, logging, and cost visibility) and validate that deployments remain compliant over time. - Monitor and optimize the cost/performance of data services (e.g., ADF, Databricks, storage) using tagging/chargeback practices, budget alerts, and right-sizing recommendations. - Secure Data Access, Identity & Governance - Define least-privilege access patterns for data services (ADF, ADLS, Azure SQL, Databricks) using Entra ID, managed identities, service principals, and RBAC—then work with administering teams to implement required changes. - Implement secure secret handling (Key Vault), encryption, and credential rotation approaches for pipelines and integrations. - Partner with network teams to meet private connectivity requirements (private endpoints, routing, firewall rules) for data sources and targets. - Ensure data integrations are production-ready and auditable (logging, lineage/documentation where applicable) and aligned to enterprise security and governance requirements. - Infrastructure Automation & Operations - Implement Infrastructure-as-Code using Terraform and/or Bicep. - Create and support CI/CD integration for both infrastructure and application or data deployments. - Set up monitoring, logging, alerting, and basic break-fix support using Azure-native tools. - Support disaster recovery planning and operational readiness for Azure resources and data services. - Vendor Enablement & Delivery Leadership - Support vendor onboarding into Azure environments, including access, permissions, deployment boundaries, and operational guardrails. - Ensure external and internal teams can deploy and operate safely without impacting core enterprise workloads. - Work closely with Hexion leads, architects, and vendors to unblock delivery and accelerate execution. - Mentor junior team members and help drive engineering maturity, documentation quality, and continuous improvement across the environment. Qualifications - Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience. - 7+ years of experience in data engineering, data integration, and production support (cloud and/or hybrid environments). - Strong hands-on expertise with Azure data services and integration patterns (ADF, ADLS, Azure SQL, Databricks, Logic Apps). - Proven experience designing and implementing Azure Data Factory pipelines and broader Azure data integration solutions. - Strong understanding of ETL, data integration, data warehousing, and production support practices. - Ability to partner with cloud platform, security, and networking teams to meet requirements for connectivity, identity, and controls needed by data workloads. - Working knowledge of Entra ID and Azure IAM concepts (RBAC, managed identities, service principals) as they apply to securing data pipelines and services. - Proficiency in SQL, Python, and PySpark. - Strong troubleshooting, communication, and collaboration skills, with the ability to operate effectively in fast-moving environments. Requirements - Azure Data & Integration: Azure Data Factory (ADF), Logic Apps, Databricks, ADLS Gen2, Azure SQL, Power BI - Languages: SQL, Python, PySpark - Security/Governance: Entra ID, RBAC, Managed Identity, Key Vault - DevOps/Operations (as applicable): CI/CD, Azure DevOps/GitHub Actions, monitoring/logging, Terraform/Bicep Preferred Qualifications - Experience with Azure SQL Database, ADLS, Databricks, and Power BI. - Experience with Infrastructure-as-Code (Terraform and/or Bicep) and automating deployments for data platforms. - Exposure to AI/ML, agentic AI, or automation-heavy Azure workloads. - Experience supporting secure multi-vendor Azure environments. - Familiarity with Azure monitoring, logging, and disaster recovery patterns. - Experience implementing or operationalizing controls aligned to ISO/IEC 27018 (protection of personally identifiable information in public clouds) is a plus. - Familiarity with SAP platforms (ECC R/3, S/4HANA, BW, and Datasphere), especially in the context of integrating SAP data into Azure. - Azure certifications such as Azure Solutions Architect Expert. - Databricks certifications such as Data Engineer Associate or Professional. - Databricks accreditations such as Databricks Fundamentals, Azure Platform Architect, or Platform Administrator. - AWS experience is a plus. Success Measures - Azure data pipelines are designed and operating reliably in production. - Delivery teams and vendors can release infrastructure builds safely using clear patterns for configuration, access, and deployment. - Stakeholders receive timely, trustworthy data through integrations that meet agreed SLAs and operational expectations. - Data quality, monitoring, and alerting are in place so issues are detected early and resolved quickly with clear ownership and runbooks. - Documentation, repeatability, and delivery maturity improve over time, reducing friction between architecture, platform teams, and delivery teams. Other We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

Company Overview Imagine Everything. Build the Future with Hexion. At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress—developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future. This is where bold thinkers, problem-solvers, and innovators come together to shape what’s next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward. We don’t follow the status quo—we challenge it, disrupt it, and improve it. Every role at Hexion is part of something bigger. We invest in innovation, sustainability, and continuous development—equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide. Your Future Starts Here. If you’re ready to push limits, reimagine what’s possible, and create the extraordinary, Hexion is where you belong. Anything is possible when you imagine everything. Position Overview This is an internal position to provide technical expertise in the field of a Chemical Engineering. This position, by way of applying past knowledge and experiences using a wide range of engineering principles, provides recommendations to help solve complex problems within the Resin processes. This position is also responsible to provide senior technical advice in the proper development of new chemical processes within a project team environment. This position will review proposed chemical processes and new recipe additions then make recommendations to ensure process requirements are met and chemical operations meet Hexion’s safety and environmental requirements. Other responsibilities include relief system modelling, providing expertise in troubleshooting existing chemical processes that are not meeting original design entitlement, commission / startup of new chemical operations and individual productivity projects to create capacity / efficiencies in existing plant processes. This position can be asked to collaborate closely with and advise different teams like Innovation, Commercial, Operations and Supply Chain. Essential Functions - Provide expertise in Process Engineering in Resin Production and process capacity - Consult and provide technical recommendations in the design of chemical processes with a focus on safety and efficiency in design. - Provides technical solutions to problems found at existing locations based upon full understanding of the products being made and the process capabilities at the site. Solutions provided need to be practical in its application as the simplest solutions tend to be the most effective. - Advising a project team of potential design or scope changes and the impact / benefit on the process. - Leveraging product understanding and process capabilities to work and advise contracted engineering groups on new process design to ensure the best possible design for any new process. - Checking calculations to advise on adherence to codes, specifications, design criteria and overall RAGAGEP (Recognized And Generally Accepted Good Engineering Practices) adherence. - Collaborate on the development of a business case for any new product / process development. Leveraging those technical skills to present a cohesive business case for Leadership approval. - Develop best practices and design standards to improve reliability and / or efficiency of existing chemical processes. - Competent in the different Process Hazardous Analysis (PHA) and hazard review techniques. Need to participate in different HAZOPs and engage teams when either reviewing old HAZOPs to ensure existing processes have not deviated from the original design or from the earliest stage of a project through commissioning. - Senior level expertise in techniques to successfully commission and startup chemical processes. - Senior level expertise in relief system modelling. - Investigate and provide written technical guidance on deviations from expected production within Hexion’s chemical processes. - Capable of organizing and leading new commissioning efforts including the closure of PSSR action items and following the MOC process. - Capable of establishing good communication channel with operation and provide education and training to upskill operation. - Capable of representing the team to Leadership on difficult technical issues in a clear and concise manner with recommendations to solve. ORGANIZATIONAL RELATIONSHIPS: This position reports to the Resin Technology Team Manager SCOPE OF RESPONSIBILITY: The Scope of Responsibility will focus on the Resin and Formaldehyde production processes. Job Qualifications & Experience - Capable of networking within a matrix organization and working remotely. - 5+ years of relevant chemical processes experience. - Must have good organizational and communication skills. - Must be familiar with process safety, environmental, and Industrial Hygiene rules and regulations associated the production of chemicals. - Capable of working with 3rd party engineering firms to represent Hexion during Front End Engineering efforts. - Worked on plant floor in chemical operating company - Analytical and Critical thinking - Batch manufacturing experience - Extensive solid material handling and equipment design. - Demonstrate project management experience especially FEL efforts. - Personal skills with the ability to communicate with different layers in the organization from the business leads to local site personnel. Important to have the ability to relate with all types of people. - Must understand the application and use of Fault Trees, Failure Mode & Effects Analysis (FMEA), Quantitative Risk Analysis (QRA), and Layer of Protection Analysis (LOPA) techniques. · Chemical Reaction Relief system modelling. Education & Skills - BS Chemical or Process Engineering - Must be able to operate Excel spreadsheets and develop PowerPoint presentations. Advance skills in Excel and intermediate skills in PowerPoint are required. - Must be able to collect data and interpret it. - Must have advanced computer skills. - Familiarity in the Stage Gate Process for projects and their front-end development. - Understand Gantt Charts and the development in Microsoft Project. - Mini-Tab experience is desired but not required. - Familiarity with enterprise system software such as SAP Travel can vary depending upon project location and requirements. Expected travel can be up 50% but can be higher pending business needs at the time. Other We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

Role Description Hexion is seeking a transformational procurement leader to architect and execute a bold reinvention of the procurement function. This is not a caretaker role. The incoming leader will inherit a function that is heavily execution-focused — reliant on manual P2P processes, disconnected market intelligence, reactive risk management, and siloed data — and will be charged with helping to build a future-state operating model centered on three pillars: - Human Value Teams — Agile "Pods" focused on Supplier Strategy, Innovation, Risk Shaping, and Business Partnering - AI Layer — AI Sourcing Agents, Predictive Analytics, Cost & Risk Models, and Autonomous Negotiations - Digital / Global Capabilities Center (GCC) Factory — Touchless P2P, Automated Tail Spend, Exceptions-Based Handling, and Clean Real-Time Data More specifically, the successful candidate will develop and lead an AI-native Center of Excellence (the AI Layer) and deploy automation throughout the Source to Pay processes. The goal: By introducing 30% of procurement work executed by AI vs. Humans, enable +3–5x more time on value creation, 30–50% reduction in process costs and cycle time, and data-driven insights for strategic advantage. This is not your average “let’s try a few AI use cases”. Our intent is to revolutionize how procurement gets done and that requires radical change in mindset, process and technology. We are not looking to improve, optimize or document. We are looking to redesign by doing. This is not the typical process of hiring an AI Leader to define the roadmap to then roll out tools process. The new leader will pick use cases, build fast, prove its value and then scale and put structure behind it. So, if you love to re-imagine procurement, fail fast while implementing and pivot equally fast, this can be your dream job. Qualifications - 12+ years of progressive procurement/supply chain leadership experience, including 3+ years at the Director or Senior Director level - Demonstrated track record of leading a procurement transformation — not just participating in one — from traditional sourcing to a digitally-enabled, strategically-focused model - Deep and proven ability to deploy AI, machine learning, or advanced analytics in a procurement context (predictive sourcing, autonomous negotiation tools, spend analytics, risk modeling) - Proven experience building and deploying AI/automation hands-on use cases (not just leading programs) - Track record of rapid prototyping and scaling digital products - Comfort working in ambiguous, fast-moving environments with minimal structure - Strong executive presence with ability to influence VP and C-suite stakeholders on transformation investments - Experience managing $300M+ in addressable spend across direct and indirect categories - Bachelor's degree required; MBA or Master's in Supply Chain, Engineering, or related field strongly preferred Requirements - Experience with agile operating models (Pods, Squads, or similar structures) in a procurement or supply chain context - Hands-on familiarity with procurement technology platforms and their AI/ML extension capabilities - Background in change management methodologies — this role requires transforming not just systems, but mindsets and ways of working - Experience with private equity-backed or sponsor-owned businesses where speed, accountability, and value creation urgency are high - CPSM, CSCP, or equivalent professional certification Benefits - Competitive base salary commensurate with experience - Annual performance bonus tied to transformation milestones and savings delivery - Long-term incentive / equity participation - Comprehensive benefits package including health, dental, vision, 401(k) match - Relocation assistance available What Success Looks Like — First 18 Months - Deploy first AI use case (e.g., predictive raw material pricing, automated tail spend) - 30 days - Complete diagnostic of current-state procurement capabilities, spend, and technology landscape - 90 days - Publish transformation roadmap with phased investment plan and quick wins - 120 days - Demonstrate measurable shift in team time allocation from execution to value creation - 18 months

Company Overview Imagine Everything. Build the Future with Hexion. At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress—developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future. This is where bold thinkers, problem-solvers, and innovators come together to shape what’s next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward. We don’t follow the status quo—we challenge it, disrupt it, and improve it. Every role at Hexion is part of something bigger. We invest in innovation, sustainability, and continuous development—equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide. Your Future Starts Here. If you’re ready to push limits, reimagine what’s possible, and create the extraordinary, Hexion is where you belong. Anything is possible when you imagine everything. Position Overview Define and own the enterprise GenAI platform strategy that makes every AI use case at Hexion possible. Build and operate reusable GenAI platform services — grounding, orchestration, memory, evaluation, and LLMOps — as production-grade shared infrastructure that accelerates delivery across Commercial, Supply Chain, R&D, and Manufacturing. Reports to Director, AI Architecture This role is the engineering foundation of Hexion’s AI transformation. The Senior Manager will build the GenAI platform layer that accelerates every use case across the enterprise — making safe, reliable, production-grade AI the default, not the exception Job Responsibilities Define and execute the enterprise GenAI technology strategy and platform roadmap, aligning capabilities to business priorities and measurable outcomes across all domains. • Lead delivery of core GenAI platform services — retrieval/grounding, knowledge foundations, memory patterns, and agent orchestration — as reusable capabilities for teams across the enterprise. • Partner with Data & Analytics to ensure AI-ready data foundations: governed access, data quality, lineage/metadata, indexing pipelines, and standardized measurement and telemetry. • Establish LLMOps and AI quality standards: evaluation frameworks, release gates, drift monitoring, and lifecycle management for prompts and models to ensure consistent performance at scale. • Embed security, privacy, Responsible AI, and compliance-by-design across all solutions through guardrails, risk reviews, auditability, and red-teaming practices. • Own operational excellence and cost governance: reliability/SLOs, incident readiness, performance optimization, model routing/caching, and dashboards that manage latency and spend. • Run AI Innovation portfolio, guide architecture and design for AI POVs, act as SME on make vs buy vs partner Attributes • Platform architect mindset — builds shared, reusable GenAI infrastructure that makes every product team faster rather than solving one-off problems. • Engineering-first and delivery-oriented — pragmatic about what ships, not just what’s architecturally elegant; known for enabling teams rather than gatekeeping them. • Security and quality conscious — treats responsible AI, compliance-by-design, and operational reliability as core platform features, not afterthoughts. • Collaborative and credible — earns trust from product teams, data scientists, security, and business leaders through technical depth and clear communication Experience • 10+ years of progressive software architecture and 3-5 years of AI/ML engineering experience; at least 3 years directly owning GenAI platform strategy, LLMOps, or enterprise AI infrastructure delivery. • Demonstrated track record shipping GenAI or distributed AI systems at enterprise scale — from architecture and platform design through LLMOps, monitoring, and continuous improvement — with measurable reliability and performance outcomes. • Experience building and leading engineering teams in transformation-stage enterprises; ideally with exposure to specialty chemicals, industrial manufacturing, or process industries and their AI/data integration patterns Preferred Qualifications: • Familiarity with AI security patterns: prompt injection defense, access controls, data governance, compliance-by-design, and cost governance for model routing and inference optimization. (Preferred) • Specialty chemicals, industrial manufacturing, or process industry experience a plus — familiarity with IoT/sensor data, SAP AI extensions, and domain-specific AI use cases. (Preferred) Knowledge, Skills, Attributes and Experience (KSAEs) •10+ years in software architecture, platform engineering, or 3-5 years AI/ML engineering; 3+ years leading GenAI or enterprise AI platform delivery at scale. • Deep expertise in the Microsoft/Azure ecosystem: Azure OpenAI, AI Foundry, Cognitive Services, Semantic Kernel, and enterprise-scale cloud architecture patterns. • Strong command of the full AI stack: experience surfaces, agentic orchestration (LangGraph, AutoGen, Semantic Kernel), knowledge/memory systems, model runtimes, evaluation frameworks, and infrastructure. • Proven track record shipping AI-driven or distributed software systems at enterprise scale, with measurable reliability, performance, and cost outcomes. • Strong understanding of hybrid AI architectures: local and cloud inference, model orchestration, multimodal runtimes, and RAG pipeline design. • Expertise in LLMOps: evaluation frameworks, release gates, prompt/model lifecycle management, drift monitoring, and responsible AI guardrails including red-teaming and auditability. • Hands-on proficiency with Azure AI Foundry, Azure OpenAI Service, Copilot Studio, and Microsoft Fabric; familiar with AKS/Kubernetes and CI/CD pipelines for AI workloads. Other We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.