Sr AI Engineer, SMART MFG & AI

Role overview

Architecture and technical ownership

• Lead end-to-end architecture, design, development, testing, deployment, and support of full-stack and AI-powered applications.
• Translate business and non-functional requirements into scalable architectures, technical designs, and executable delivery plans.
• Own complex features, services, and platforms from initial design through production deployment and ongoing support.
• Evaluate architecture tradeoffs involving scalability, reliability, security, cost, maintainability, and delivery timelines.
• Maintain architecture documents, technical specifications, API contracts, data flows, and decision records.
• Identify technical risks and drive alignment across engineering, architecture, data science, platform, security, and product teams.

Full-stack and AI engineering

• Develop secure backend services and REST APIs using C#, .NET, and ASP.NET Core.
• Build responsive, accessible, reusable frontend components using frameworks such as Angular, React, Blazor, or Vue.js.
• Develop APIs, microservices, event-driven services, and enterprise integration components.
• Integrate large language models and Generative AI capabilities into applications.
• Establish practices for software quality, security, reliability, observability, development velocity, and production support readiness.

Technical domains

• The role combines software engineering, Generative AI, Agentic AI, cloud-native engineering, data platforms, APIs, and modern user experiences.
• The description names Large Language Models, Retrieval-Augmented Generation, and Model Context Protocol among relevant technologies.
• The source description is truncated after beginning a list of enterprise AI technologies.

Collaboration and leadership

Requirements

• Experienced software engineer with practical experience in artificial intelligence, cloud-native application development, data integration, and enterprise solution delivery.
• Strong software engineering expertise and hands-on experience with Generative AI, Agentic AI, cloud-native engineering, data platforms, APIs, and modern user experiences.
• Ability to independently own complex technical outcomes, influence architecture decisions, guide engineering practices, and collaborate across teams.
• Experience developing backend services and APIs using C#, .NET, and ASP.NET Core.
• Experience developing frontend applications using a framework such as Angular, React, Blazor, or Vue.js; these are listed as alternatives.
• Ability to mentor junior engineers and deliver reliable, maintainable solutions.