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.