AI Engineer

Sealed Air is seeking a hands-on Senior AI Engineer to design, develop, deploy, and support AI-enabled applications for supply chain and manufacturing operations. The role combines software engineering and solution architecture with predictive machine learning, industrial IoT, MES integration, and generative AI to improve equipment reliability, work center performance, product quality, and operational productivity.

The engineer will partner with supply chain leaders, plant operations, maintenance, OT, data engineering, and IT teams to turn business problems into secure, reliable production solutions and measurable outcomes.

• Manufacturing AI and predictive analytics. Develop and operationalize ML solutions for predictive maintenance, anomaly detection, equipment failure risk, cycle time and throughput forecasting, quality prediction, and work center bottleneck analysis. Define baselines and measure operational impact with plant stakeholders.
• Industrial data and MES integration. Integrate machine and sensor telemetry, historian data, MES events, maintenance records, and ERP data. Connect equipment signals with production orders, assets, work centers, downtime reasons, and quality results to create meaningful analytical features.
• Model engineering and lifecycle. Build reproducible data preparation, training, evaluation, deployment, and retraining pipelines. Address time-series alignment, missing data, data leakage, class imbalance, and changing operating conditions; monitor model drift, false alarms, and prediction quality.
• LLM and RAG applications. Build applications using LLMs, embeddings, vector search, and retrieval-augmented generation (RAG) for manufacturing knowledge, troubleshooting, and operational assistance. Evaluate retrieval quality, grounded responses, access controls, latency, and cost.
• AI automation. Develop AI-assisted workflows that turn predictions and retrieved knowledge into alerts, recommendations, maintenance requests, and approved business actions. Apply human review, auditability, and appropriate OT controls to actions affecting plant operations.
• Full stack engineering and Azure operations. Design and build APIs, backend services, databases, and web interfaces. Deploy, configure, monitor, troubleshoot, and support applications in Azure App Service, including identity, secrets, networking dependencies, availability, and application performance.
• DevOps and production ownership. Use Azure DevOps for source control, work tracking, pull requests, automated testing, and CI/CD across development, test, and production. Maintain deployment approvals, rollback procedures, monitoring, incident diagnostics, and support documentation.
• Technical leadership and collaboration. Translate business needs into technical designs and delivery plans; conduct code reviews, mentor engineers, and establish reusable patterns. Use approved AI coding tools and validate generated code for security, correctness, and maintainability.

Candidates must demonstrate hands-on capability across all areas below. Experience limited to AI tool usage, proofs of concept, or managerial oversight does not meet the requirements.

• Engineering background. Bachelor's degree in Computer Science, Engineering, Data Science, or a related field; 10+ years of overall IT experience, including 7+ years of hands-on software development. Demonstrated solution design and architecture experience.
• Supply chain and manufacturing domain. Strong understanding of production planning and execution, work centers, asset maintenance, quality, inventory, and material flow. Ability to translate downtime, throughput, yield, scrap, and overall equipment effectiveness (OEE) into practical AI use cases and success measures.
• Industrial IoT and MES. Strong understanding and practical experience with industrial IoT and Manufacturing Execution Systems (MES), including machine connectivity, sensor telemetry, production events, equipment states, and IT/OT integration. Understand edge-to-cloud data flow and industrial messaging or connectivity patterns such as MQTT or OPC UA.
• Experience with Azure AI services, Azure Machine Learning, Azure AI Search, Microsoft Fabric, and production MLOps or LLMOps practices. (Preferred)
• Experience integrating SAP or other ERP platforms with MES, historians, maintenance systems, and event-driven services; familiarity with industrial edge deployments. (Preferred)
• Predictive AI and ML engineering. Hands-on experience building and deploying predictive models using machinery, work center, or manufacturing process data. Strong Python, SQL, feature engineering, time-series analysis, model validation, and ML framework skills; ability to integrate model outputs into operational workflows.
• LLMs and RAG. Demonstrated experience developing AI applications using LLMs and RAG, including document ingestion, chunking, embeddings, retrieval, prompt design, API integration, and evaluation. Understand hallucination risks, prompt injection, data privacy, and permission-aware retrieval.
• Azure application management. Hands-on experience deploying and operating web applications in Azure App Service. Understand Microsoft Entra app registrations, service principals, managed identities, authentication and authorization, Key Vault, and Azure role-based access control. Understand VNets, subnets, private endpoints, DNS, and App Service network integration sufficiently to troubleshoot application connectivity with infrastructure teams.
• Azure DevOps. Working proficiency with Azure Repos or Git repositories integrated with Azure DevOps, Boards, pull requests, branching, CI/CD pipelines, service connections, environment configuration, release approvals, and rollback practices.
• Software engineering and collaboration. Strong hands-on Python for AI/ML and deep expertise in at least one primary backend stack: Python, .NET/C#, or Java. Experience with APIs, databases, automated testing, production troubleshooting, and modern web interfaces. Communicate clearly with plant, business, and technical teams and mentor engineers.
• Experience with Azure AI services, Azure Machine Learning, Azure AI Search, Microsoft Fabric, and production MLOps or LLMOps practices is preferred.
  Experience integrating SAP or other ERP platforms with MES, historians, maintenance systems, and event-driven services; familiarity with industrial edge deployments is preferred.

Base Compensation: $93,100 - $160,655 + bonus eligibility

The range disclosed complies with applicable state and local pay transparency laws. Offers within this range will be determined by considering relevant factors including education, experience, and internal alignment. This position may also be eligible for annual performance bonuses and other incentive programs. Sealed Air offers a competitive benefits package that includes health, dental, vision, 401(k), paid time off, and other benefits designed to promote well-being.