Hexion is looking for a Director, AI Architecture & Engineering to own the full-stack AI engineering and architectural foundation that powers our Chemicals-as-a-Service (CaaS) transformation. You will 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.
What You'll Do
- Define and own Hexion’s enterprise AI architecture: multi-agent frameworks, LLM/GenAI platforms, ML pipelines, data layer, and integration patterns across SAP S/4HANA, Salesforce, OSIsoft PI, and cloud environments (Azure/AWS).
- Build and scale the agentic AI platform: multi-agent orchestration (LangGraph/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.
What We're Looking For
- 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 (LangGraph, CrewAI, AutoGen), and multi-agent orchestration at enterprise scale.
- MLOps mastery: model lifecycle management, CI/CD for ML, drift monitoring, feature stores, model registries (MLflow, Kubeflow, SageMaker, 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/4HANA, Salesforce or Dynamics 365).
- Responsible AI engineering: XAI/explainability, bias detection, prompt injection defense, AI security, and compliance frameworks relevant to specialty chemicals (REACH, GHS, data sovereignty).
- High level of proficiency with ERP and advanced planning systems (SAP IBP, S/4HANA, APO, o9, Kinaxis).
- Python/SQL fluency; working knowledge of ML frameworks (PyTorch, scikit-learn, HuggingFace); ability to review and contribute to production AI code.
Nice to Have
- Prior experience building AI teams from the ground up in transformation-stage or industrial enterprises; track record of hiring and growing ML engineers and data engineers.
Technical Stack
- SAP S/4HANA, Salesforce, OSIsoft PI
- Azure, AWS
- LangGraph, CrewAI, AutoGen
- Kafka, MLflow, Kubeflow, SageMaker, Azure ML
- Docker, Kubernetes
- Python, SQL, PyTorch, scikit-learn, HuggingFace
Team & Environment
You will build and lead the AI engineering team, which includes ML engineers, data engineers, LLM engineers, MLOps specialists, and AI platform engineers. In this role, you will serve as the technical authority connecting AI CoE, IT, and domain teams (R&D, commercial, manufacturing). You will report directly to the VP/Director, AI Transformation.
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.
