Q
Senior AI Engineer
Qnity Electronics, Inc.
1 hour ago
Full-time
On-site
Wilmington, Delaware, United States
您是否渴望助力激动人心的先进电子领域的下一次飞跃？ 您是否希望跟我们一起解决难题， 共同推动电子技术和互联科技的快速发展？那么，带着您的解决问题的能力、热情和创造力，与我们一起推动电子领域的下一次飞跃。
在启诺迪，我们不仅是先进电子和高科技领域材料及解决方案的全球领导者，更是一个紧密团结、充满激情、勇于挑战的团队。我们所有敬业的团队都致力于将尖端技术变为现实。我们重视具有前瞻性思维的挑战者、突破界限的开拓者以及各个部门的多元化视角，因为我们深知，我们在推动世界进步、造福全人类方面扮演着至关重要的角色。了解如何加入我们，开启或加速您的职业生涯。
Senior AI Engineer
Qnity is accepting applications for a full-time
Senior AI Engineer
position based at one of Qnity’s main campuses in
Wilmington, Delaware, USA .
For engineers who want to take generative AI beyond experimentation and into daily production use, this is an exciting opportunity to join a growing team that plays a vital and dynamic role in the company.
Qnity is a market leader in specialty materials for electronic devices and microchip fabrication. In this role, the Senior AI Engineer will collaborate with data scientists, operations scientists, and Digital and IT teams engaged in a variety of manufacturing and business activities, building the agentic AI and enterprise retrieval capabilities these teams depend on.
Generative AI, agent orchestration, and enterprise search are becoming core to business operations, creating opportunities to contribute across:
Enterprise agentic AI platform architecture
Retrieval-augmented generation (RAG) over proprietary technical and business content
Multi-agent automation for business and manufacturing workflows
Secure, permission-aware enterprise data access
Production deployment, evaluation, observability, and AI cost optimization
A strong candidate will bring modern AI engineering expertise in LLM application design, retrieval and ranking, agent orchestration, prompt engineering, evaluation, and machine learning. The role requires strong Python skills to prepare and index data, build and serve models and agents, and create clear documentation and demonstrations.
The Senior AI Engineer will also plan delivery, lead technical work, communicate with business stakeholders, integrate with data engineering and software teams, deploy production solutions, and coach the broader community.
Key Responsibilities
Partner with business stakeholders to define use cases, scope, and success criteria, and translate business problems into AI, machine learning, or computer vision solutions.
Lead end-to-end AI delivery, including architecture, technical direction, code quality, deployment, operations, reliability, performance, and cost.
Architect and operate the enterprise agentic AI platform on Azure AI Foundry, optimizing models, orchestration, retrieval, evaluation, latency, scale, and cost.
Design enterprise RAG over SharePoint and Microsoft 365 content using Microsoft Graph, permission-aware ingestion, embeddings, metadata, re-ranking, and access-controlled search.
Build Copilot Studio agents, custom connectors, Microsoft 365 Copilot and Teams agents, MCP servers, and function-calling tools for governed enterprise actions.
Design multi-agent patterns, including orchestrator-worker delegation, sequential and concurrent execution, handoff, collaboration, state management, and memory.
Develop and evaluate AI applications for knowledge discovery, workflow automation, quality improvement, process monitoring, defect detection, and operational efficiency.
Collaborate with data engineering, software, and digital teams to integrate enterprise data, build scalable pipelines, and deliver production solutions through CI/CD.
Set enterprise AI engineering standards, reusable architecture patterns, and design-review practices that reduce production risk.
Communicate results, coach engineers and data scientists, and drive adoption through responsible AI, user feedback, and continuous improvement.
Required Skills & Education
Bachelor’s degree or higher in data science, computer science, engineering, or a related technical field.
1+ years of experience building and deploying production AI and machine learning systems.
Strong Python development skills, with SQL/NoSQL experience. Java or R experience is a plus.
Hands-on Azure AI experience, including Azure AI Foundry, Azure OpenAI, Azure AI Document Intelligence, Agent Service, Prompt Flow, evaluation, embeddings, and content safety.
Advanced RAG and search skills, including Azure AI Search, hybrid/vector retrieval, semantic ranker, chunking, metadata filtering, re-ranking, and document-level security trimming.
Experience with Microsoft Graph, SharePoint Online, Microsoft 365 content, Entra ID app registrations, delegated/application permissions, and ACL-based access control.
Copilot and agent extensibility experience with Copilot Studio, Microsoft 365 Copilot and Teams agents, MCP servers, custom connectors, function-calling tools, Adaptive Cards, Graph connectors, and governed enterprise integrations.
Agent orchestration experience with Microsoft Agent Framework, Semantic Kernel, Azure AI Foundry Agent Service, LangChain/LangGraph, planner-executor patterns, ReAct loops, tool calling, and guardrails.
Applied ML, NLP, and computer vision foundation, including supervised and unsupervised learning, feature engineering, transformers, deep learning, object detection, and image segmentation.
Production AI engineering experience with LLMOps/MLOps, evaluation, regression testing, observability, tracing, CI/CD, Docker, Kubernetes, Azure DevOps, Azure Functions, AKS/Container Apps, API Management, Key Vault, Application Insights, and Azure Monitor.
Working knowledge of enterprise AI security and governance, including permission trimming, data residency, Purview sensitivity labels, DLP, responsible AI, prompt-injection defenses, and cost controls.
Strong technical leadership, architecture review, mentoring, stakeholder communication, and delivery ownership skills.
Preferred Experience
Experience in manufacturing, semiconductor, specialty materials, or operational technology environments.
Living the Qnity Values At Qnity, success is measured not only by
what
we achieve, but also by
how
we achieve it.
Customer:
Partner with stakeholders to understand needs, solve business challenges, and deliver meaningful outcomes.
Innovation:
Continuously improve processes, technologies, and ways of working.
Speed:
Act with urgency, focus, and precision to move work forward and deliver results.
People:
Build trusted relationships, collaborate across teams, and inspire positive change.
加入我们的人才社区 并与我们保持联系！https://careers.qnityelectronics.com/cn/zh/jointalentcommunity
Qnity是一家推崇机会均等的公司。我们对符合条件的求职者一视同仁，不会因其种族、肤色、宗教、信条、性别、性取向、性别认同、婚姻状况、国籍、年龄、退伍军人身份、残疾或或属于任何其他受保护阶层而区别对待。如果您需要借助合理的便利条件来搜索或申请职位，请访问我们的无障碍功能页面获取联系信息。http://www.qnityelectronics/accessibility.html
Qnity提供全面的薪资和福利方案。要了解更多，请访问薪酬和福利页面 https://careers.qnityelectronics.com/cn/zh/compensation-and-benefits-final
我們使用人工智慧（AI）來增強我們的招聘流程。
#J-18808-Ljbffr
在启诺迪，我们不仅是先进电子和高科技领域材料及解决方案的全球领导者，更是一个紧密团结、充满激情、勇于挑战的团队。我们所有敬业的团队都致力于将尖端技术变为现实。我们重视具有前瞻性思维的挑战者、突破界限的开拓者以及各个部门的多元化视角，因为我们深知，我们在推动世界进步、造福全人类方面扮演着至关重要的角色。了解如何加入我们，开启或加速您的职业生涯。
Senior AI Engineer
Qnity is accepting applications for a full-time
Senior AI Engineer
position based at one of Qnity’s main campuses in
Wilmington, Delaware, USA .
For engineers who want to take generative AI beyond experimentation and into daily production use, this is an exciting opportunity to join a growing team that plays a vital and dynamic role in the company.
Qnity is a market leader in specialty materials for electronic devices and microchip fabrication. In this role, the Senior AI Engineer will collaborate with data scientists, operations scientists, and Digital and IT teams engaged in a variety of manufacturing and business activities, building the agentic AI and enterprise retrieval capabilities these teams depend on.
Generative AI, agent orchestration, and enterprise search are becoming core to business operations, creating opportunities to contribute across:
Enterprise agentic AI platform architecture
Retrieval-augmented generation (RAG) over proprietary technical and business content
Multi-agent automation for business and manufacturing workflows
Secure, permission-aware enterprise data access
Production deployment, evaluation, observability, and AI cost optimization
A strong candidate will bring modern AI engineering expertise in LLM application design, retrieval and ranking, agent orchestration, prompt engineering, evaluation, and machine learning. The role requires strong Python skills to prepare and index data, build and serve models and agents, and create clear documentation and demonstrations.
The Senior AI Engineer will also plan delivery, lead technical work, communicate with business stakeholders, integrate with data engineering and software teams, deploy production solutions, and coach the broader community.
Key Responsibilities
Partner with business stakeholders to define use cases, scope, and success criteria, and translate business problems into AI, machine learning, or computer vision solutions.
Lead end-to-end AI delivery, including architecture, technical direction, code quality, deployment, operations, reliability, performance, and cost.
Architect and operate the enterprise agentic AI platform on Azure AI Foundry, optimizing models, orchestration, retrieval, evaluation, latency, scale, and cost.
Design enterprise RAG over SharePoint and Microsoft 365 content using Microsoft Graph, permission-aware ingestion, embeddings, metadata, re-ranking, and access-controlled search.
Build Copilot Studio agents, custom connectors, Microsoft 365 Copilot and Teams agents, MCP servers, and function-calling tools for governed enterprise actions.
Design multi-agent patterns, including orchestrator-worker delegation, sequential and concurrent execution, handoff, collaboration, state management, and memory.
Develop and evaluate AI applications for knowledge discovery, workflow automation, quality improvement, process monitoring, defect detection, and operational efficiency.
Collaborate with data engineering, software, and digital teams to integrate enterprise data, build scalable pipelines, and deliver production solutions through CI/CD.
Set enterprise AI engineering standards, reusable architecture patterns, and design-review practices that reduce production risk.
Communicate results, coach engineers and data scientists, and drive adoption through responsible AI, user feedback, and continuous improvement.
Required Skills & Education
Bachelor’s degree or higher in data science, computer science, engineering, or a related technical field.
1+ years of experience building and deploying production AI and machine learning systems.
Strong Python development skills, with SQL/NoSQL experience. Java or R experience is a plus.
Hands-on Azure AI experience, including Azure AI Foundry, Azure OpenAI, Azure AI Document Intelligence, Agent Service, Prompt Flow, evaluation, embeddings, and content safety.
Advanced RAG and search skills, including Azure AI Search, hybrid/vector retrieval, semantic ranker, chunking, metadata filtering, re-ranking, and document-level security trimming.
Experience with Microsoft Graph, SharePoint Online, Microsoft 365 content, Entra ID app registrations, delegated/application permissions, and ACL-based access control.
Copilot and agent extensibility experience with Copilot Studio, Microsoft 365 Copilot and Teams agents, MCP servers, custom connectors, function-calling tools, Adaptive Cards, Graph connectors, and governed enterprise integrations.
Agent orchestration experience with Microsoft Agent Framework, Semantic Kernel, Azure AI Foundry Agent Service, LangChain/LangGraph, planner-executor patterns, ReAct loops, tool calling, and guardrails.
Applied ML, NLP, and computer vision foundation, including supervised and unsupervised learning, feature engineering, transformers, deep learning, object detection, and image segmentation.
Production AI engineering experience with LLMOps/MLOps, evaluation, regression testing, observability, tracing, CI/CD, Docker, Kubernetes, Azure DevOps, Azure Functions, AKS/Container Apps, API Management, Key Vault, Application Insights, and Azure Monitor.
Working knowledge of enterprise AI security and governance, including permission trimming, data residency, Purview sensitivity labels, DLP, responsible AI, prompt-injection defenses, and cost controls.
Strong technical leadership, architecture review, mentoring, stakeholder communication, and delivery ownership skills.
Preferred Experience
Experience in manufacturing, semiconductor, specialty materials, or operational technology environments.
Living the Qnity Values At Qnity, success is measured not only by
what
we achieve, but also by
how
we achieve it.
Customer:
Partner with stakeholders to understand needs, solve business challenges, and deliver meaningful outcomes.
Innovation:
Continuously improve processes, technologies, and ways of working.
Speed:
Act with urgency, focus, and precision to move work forward and deliver results.
People:
Build trusted relationships, collaborate across teams, and inspire positive change.
加入我们的人才社区 并与我们保持联系！https://careers.qnityelectronics.com/cn/zh/jointalentcommunity
Qnity是一家推崇机会均等的公司。我们对符合条件的求职者一视同仁，不会因其种族、肤色、宗教、信条、性别、性取向、性别认同、婚姻状况、国籍、年龄、退伍军人身份、残疾或或属于任何其他受保护阶层而区别对待。如果您需要借助合理的便利条件来搜索或申请职位，请访问我们的无障碍功能页面获取联系信息。http://www.qnityelectronics/accessibility.html
Qnity提供全面的薪资和福利方案。要了解更多，请访问薪酬和福利页面 https://careers.qnityelectronics.com/cn/zh/compensation-and-benefits-final
我們使用人工智慧（AI）來增強我們的招聘流程。
#J-18808-Ljbffr