AI Engineering Manager

Solstice Advanced Materials•Morris Plains, NJ

17h•$201,063 - $251,622•Onsite

About The Position

The AI Engineering Manager at Solstice Advanced Materials leads AI initiatives across business functions and technology platforms, translating AI and automation research into practical enterprise solutions. This hands-on leadership role combines technical expertise, team guidance, and cross-functional partnership to advance operational efficiency and strategic outcomes. The manager leads enterprise AI systems and initiatives across areas including Supply Chain, Finance, Commercial, Customer Experience, Legal, and HR, and helps move AI and automation from insights to action. The role oversees the design, development, and implementation of scalable, performant AI solutions aligned with enterprise objectives. It includes implementing MLOps/LLMOps and cloud DevSecOps practices, packaging AI solutions for production, accelerating applied AI through rapid iteration, and guiding responsible AI adoption in partnership with the Corporate AI Risk Council. The manager promotes evaluation and observability, continuous-learning systems, secure and classification-aware adoption standards, and effective collaboration among business, technology, architecture, and security teams. The position is based in Morris Plains, New Jersey, and reports to the Director IT, AI, Analytics & Automation.

Requirements

At least 8 years of progressive experience in AI solution delivery, with demonstrated impact across multiple functional domains.
Strong understanding of core AI concepts, foundational principles, and hands-on applications, including experience productionizing enterprise-grade solutions.
Proficiency with multiple AI/ML and automation tools, such as Azure AI/Microsoft Foundry, Databricks, Cognitive Services and Bot Frameworks, Microsoft Power Platform, Workato, OutSystems, or Automation Anywhere or similar tools.
Experience integrating enterprise platforms such as SAP, SFDC, and HCM with AI and automation solutions.
A proven track record developing and architecting end-to-end AI and automation solutions that integrate multiple systems and deliver measurable business value.

Nice To Haves

Python experience for AI/ML workflows.
Experience building agent-based systems with tool use, reasoning workflows, and API orchestration.
Experience developing AI applications with LLM integrations, prompt engineering, and orchestration frameworks.
Understanding of AI security practices, including RBAC/ABAC, audit logging, and prompt-level safeguards.
Experience optimizing vector databases and semantic search technologies for large datasets.
Experience with compound AI architectures, retrieval pipelines, and Azure/Databricks DevOps or MLOps practices.
Experience integrating AI solutions into enterprise channels such as Teams, Web Chat, or Direct Line.
Ability to quickly understand new functional domains, technical environments, business processes, and requirements and translate them into effective automation solutions.
Strong analytical thinking and creative problem-solving skills in complex technical and business contexts.
Ability to explain AI technical concepts to audiences at varying levels.
Ownership, pride in work, attention to detail, and willingness to work in a diverse, cross-functional environment.
Ability to partner with diverse stakeholders, identify automation improvements, and understand data needs across discrete and continuous manufacturing processes.
Experience working closely with managed services providers to support and manage automation processes effectively.
Prior publications in top-tier journals or conferences such as NeurIPS, AAAI, EMNLP, MICA, or similar.

Responsibilities

Lead and manage a team of AI engineers delivering high-quality, innovative AI solutions.
Design, develop, and implement AI algorithms, models, and enterprise systems that address business challenges and meet complex requirements for scalability, performance, and alignment with enterprise objectives.
Serve as a hands-on subject matter expert across AI and Gen AI technologies, applying technical and business understanding to deliver enterprise-grade solutions.
Implement MLOps/LLMOps and cloud DevSecOps practices, and package AI solutions for production.
Oversee Gen AI, classical AI, and automation initiatives across functions including Supply Chain, Finance, Commercial, Customer Experience, Legal, and HR.
Accelerate applied AI initiatives through rapid iteration from idea to execution in accordance with responsible AI principles.
Guide and technically steer the Corporate AI Risk Council, balancing risk, compliance, and speed for Gen AI adoption.
Promote evaluation and observability, and develop a roadmap for a robust data flywheel and continuous-learning systems.
Partner with business, technology, architecture, and security teams to identify automation opportunities and deliver secure, scalable AI solutions.
Develop practical standards and guidance for responsible, classification-aware AI and Gen AI adoption.
Translate AI research and engineering advances into actionable strategy and robust, reliable, enterprise-ready solutions.
Collaborate with cross-functional teams to integrate AI solutions into existing systems and processes.
Provide technical leadership and guidance to team members, ensuring AI development best practices.
Monitor industry trends, emerging technologies, and AI advancements to drive continuous improvement.