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Qnity

Senior AI Engineer

Wilmington, DE, United States

Apply on careers.qnityelectronics.com About employer

Applications open in a new tab.

Job details

Experience: 1+ years of experience building and deploying production AI and machine learning systems.
Posting language: English
Posted: Nov 11, 2026

Original job description

Are you looking to power the next leap in the exciting world of advanced electronics? Do you want to help solve problems that drive success in the rapidly evolving technology and connectivity landscape? Then bring your problem-solving, passion, and creativity to help us power the next leap in electronics.

At Qnity, we’re more than a global leader in materials and solutions for advanced electronics and high-tech industries – we’re a tight-knit team that is motivated by new possibilities, and always up for a challenge. All our dedicated teams contribute to making cutting-edge technology possible. We value forward-thinking challengers, boundary-pushers, and diverse perspectives across all our departments, because we know we play a critical role in the world enabling faster progress for all. Learn how you can start or jumpstart your career with us.

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 ValuesAt 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.

Join our Talent Community to stay connected with us!

Qnity is an equal opportunity employer. Qualified applicants will be considered without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability or any other protected class. If you need a reasonable accommodation to search or apply for a position, please visit our Accessibility Page for Contact Information.

Qnity offers a comprehensive pay and benefits package. To learn more visit the Compensation and Benefits page.

We use Artificial Intelligence (AI) to enhance our recruitment process.

Apply on careers.qnityelectronics.com About employer

More about this job

Skills

Python
Data engineering
Microsoft Azure
Microsoft SharePoint
Microsoft 365
Microsoft Teams
CI/CD
Process improvement
Computer science
Machine learning
SQL
NoSQL
LangChain
ML
Natural language processing
Deep learning
Docker
Kubernetes
DevOps
Leadership
Coaching
Communication skills
Improve business processes
Compensation and benefits

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Work requirements

Jobs in the United States