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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** QNity, Inc. - **Location:** Wilmington, DE, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Integration Architecture, Application Performance Management, Computer Vision, Automation of Tests, Microsoft Azure, Cloud Computing, Cloud Computing Security, Cloud Storage, Cyber Security, Continuous Integration, Data Validation, Information Engineering, Digital Technology, Distributed Systems, Github, Python (Programming Language), Key Management, Machine Learning, Microsoft SQL Server, MongoDB, Natural Language Processing, Object Detection, OpenCV, Performance Tuning, Software Architecture, Role-Based Access Control, OpenAI, Cloud Services, Tensorflow, Microsoft Copilot, Standard Sql, Search Technologies, Software Engineering, Systems Integration, Unstructured Data, Video Editing, Enterprise Search, Microsoft Agent Framework, Data Logging, Cloud Platform System, Pytorch, Power Platform Integration, Office365, Retrieval-Augmented Generation, Multi-Agent Systems, Software Security, Deep Learning, Model Validation, Generative AI, Convolutional Neural Networks, Backend, Agentic-AI, Fastapi, Microsoft Copilot Studio, Data Lakes, AI Platforms, Information Technology, Deployment Automation, Google Cloud Functions, Cosmos DB, Apache Nifi, Machine Learning Operations, Feature Extraction, Azure AI, Api Design, Restful APIs, Software Version Control, Data Pipelines, Key Vault, Databricks, Microservices - **Published:** November 13, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=1c82d2fd5944b6e2 ## About the Role * A bachelor's degree or higher in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, or a closely related field, plus at least one year of progressive experience in AI engineering, backend software development, machine learning engineering, data engineering, or related enterprise technology development. * Strong knowledge of AI system design, agent orchestration, machine learning, natural language processing, software architecture, API design, distributed systems, cloud security, CI/CD, observability, performance optimization, production reliability, and cross-functional technical communication. * Experience with Microsoft Azure technologies, including Azure OpenAI, AI Search, Function Apps, App Service, Blob/Data Lake Storage, Key Vault, Application Insights, Entra ID, RBAC, and managed identities. * Experience building enterprise data solutions using Azure Cosmos DB, SQL Server, MongoDB, Databricks, Apache NiFi, document repositories, APIs, and cloud storage. * Strong Copilot and agent extensibility experience with Copilot Studio, Microsoft 365 Copilot/Teams agents, MCP servers, custom connectors, function-calling tools, Adaptive Cards, Graph connectors, and governed enterprise integrations. * Advanced Python and SQL skills, with experience in FastAPI, microservices, REST APIs, asynchronous applications, data validation, automated testing, and enterprise integrations. * Hands-on experience designing and deploying generative AI, agentic AI, retrieval-augmented generation (RAG), enterprise search, and Copilot or agent extensibility solutions using modern AI platforms, frameworks, model services, and tool-integration patterns. * Hands-on experience with computer vision and deep learning using PyTorch or TensorFlow, YOLO, OpenCV, convolutional neural networks, object detection, tracking, image or video processing, and model evaluation. * Experience with CI/CD, automated testing, source control, observability, application security, performance optimization, and production support using Azure DevOps or GitHub. * Strong communication skills, with the ability to translate business requirements into technical designs and collaborate with software, data, security, cloud, and business teams. ## Description Qnity is a market leader in specialty materials for electronic devices and microchip fabrication. In this role, the Senior AI Engineer will collaborate with business, engineering, cloud platform, data engineering, and digital technology teams to architect, develop, integrate, deploy, and operate enterprise artificial intelligence platforms and backend systems. AI and software engineering are integral to Qnity's digital transformation, with opportunities for senior-level contributions in: * Enterprise AI platforms, agent orchestration, retrieval-augmented generation (RAG), and application integration * Python and FastAPI backend services, APIs, and data pipelines * Machine learning, deep learning, and computer vision solutions The successful candidate will have experience delivering secure, production-grade AI applications and translating business requirements into reusable architectures, backend services, APIs, data pipelines, and cloud solutions. The role combines generative and agentic AI, retrieval-augmented generation, deep learning, computer vision, and backend software engineering. The candidate will provide technical leadership across design, development, testing, deployment, monitoring, security, performance, and continuous improvement., * Architect and maintain AI platforms and backend services using Python, FastAPI, microservices, REST APIs, asynchronous processing, and secure integration patterns. * Define and implement the architecture for Qnity's enterprise agentic AI platform using Microsoft Foundry, Azure AI Agent Service, and Microsoft Agent Framework, with reusable service, orchestration, security, and governance patterns. * Design, build, deploy, and support generative AI agents and retrieval-augmented generation solutions for enterprise knowledge use cases, integrating structured and unstructured data through semantic, vector, hybrid, metadata-filtered, and permission-aware search. * Develop computer vision and deep learning applications for image and video analysis, including object detection, tracking, feature extraction, anomaly detection, and model evaluation. * Implement identity, access control, secrets management, automated testing, deployment automation, logging, monitoring, performance, and reliability controls using Microsoft Azure cloud engineering and security practices. * Partner with business, scientific, software, data engineering, information security, and cloud teams to define requirements, prototype solutions, resolve integration and production issues, document architectures and APIs, and guide technical delivery.