Senior Manager AI Architecture Innovation

About the role

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 POV's, 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; 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.
• Specialty chemicals, industrial manufacturing, or process industry experience a plus — familiarity with IoT/sensor data, SAP AI extensions, and domain-specific AI use cases.