Director, AI Architecture & Engineering - US Remote

Location: Millersburg


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.


Role Mission


Own the full-stack AI engineering and architecture foundation that powers Hexion's CaaS transformation. Design, build, and operate the enterprise AI platform - spanning data infrastructure, ML/LLM
pipelines, agentic systems, MLOps, and AI governance - that enables every domain (Commercial, R&D, Manufacturing, Supply Chain) to deploy production-grade AI at speed.


Job Responsibilities

• Define and own Hexion's enterprise AI architecture: multi-agent frameworks, LLM/GenAI platforms, ML pipelines, data
  layer, and integration patterns across SAP S/4
  
  HANA, Salesforce, OSIsoft PI, and cloud environments (Azure/AWS).
• Build and scale the agentic AI platform: multi-agent orchestration (Lang Graph/CrewAI), RAG pipelines, tool-calling
  frameworks, guardrails, and human-in-the-loop controls for autonomous workflows across business functions.
• Establish and operate enterprise MLOps: model registry, CI/CD for AI, model versioning, drift monitoring, inference
  optimization, and closed-loop retraining pipelines - ensuring all models are production-grade and auditable.
• Architect the data foundation for AI: feature stores, semantic/vector layers, real-time streaming (Kafka/event-driven), data
  quality pipelines, and synthetic data generation for specialty chemicals use cases.
• Lead AI security and responsible AI engineering: prompt injection defense, model explainability (XAI), bias detection,
  access controls, and compliance with enterprise data policy and regulatory requirements (REACH, GHS, SOX).
• Serve as the technical authority connecting AI CoE, IT, domain teams (R&D, commercial, manufacturing), and external
  vendors - translating business requirements into scalable AI system designs.
• Evaluate and manage AI technology vendors, cloud providers, and open-source frameworks; make strategic
  buy/build/partner decisions for the AI stack with clear cost, capability, and risk analysis.
• Build and lead the AI engineering team: ML engineers, data engineers, LLM engineers, MLOps specialists, and AI
  platform engineers - hiring, mentoring, and creating a culture of engineering excellence.
• Champion engineering standards: modular/reusable AI solution patterns, API-first design, observability, SRE practices for
  AI systems, and documentation to accelerate cross-functional deployment.
• Drive Hexion's Perception Intelligence, Predictive Modeling, and Adaptive Closed-Loop Control capabilities - including
  sensor fusion from OSIsoft PI, digital twin integration, and process optimization AI for manufacturing.
• Own the AI infrastructure roadmap - balancing rapid experimentation and disciplined production delivery - and report
  engineering KPIs, platform reliability, and build-vs-buy decisions to VP/Director, AI Transformation (Sambit).

Knowledge, Skills, Attributes and Experience (KSAEs)

• 10+ years in AI/ML engineering, data engineering, or enterprise architecture; 3+ years in a senior technical leadership role owning an AI platform or engineering
  team.
• Deep expertise in GenAI/LLM systems: RAG, fine-tuning, prompt engineering, agentic frameworks (Lang Graph, CrewAI, Auto Gen), and multi-agent
  orchestration at enterprise scale.
• MLOps mastery: model lifecycle management, CI/CD for ML, drift monitoring, feature stores, model registries (MLflow, Kubeflow, Sage Maker, Azure ML), and
  inference optimization.
• Cloud-native AI infrastructure:
  Azure/AWS AI services, containerized ML workloads (Docker/Kubernetes), event-driven architecture (Kafka), APIs, IaC, and
  observability/SRE practices.
• Data architecture for AI: feature engineering, vector/semantic layers, real-time streaming, data quality pipelines, and integration with industrial systems (OSIsoft
  PI, SAP S/4
  
  HANA, Salesforce or Dynamics 365).
• Responsible AI engineering:…