AI Full Stack Engineer

Micron Technology•Boise, ID

About The Position

Micron Technology is seeking an AI Full Stack Engineer to design, develop, test, deploy, and support modern applications that incorporate AI as a core capability. The role combines full stack software engineering with AI-native development practices, including custom agent development, prompt engineering, Model Context Protocol (MCP) integrations, and AI-assisted software delivery to improve development efficiency and business outcomes. The engineer will build and support scalable, secure, and reliable applications and AI assistants that improve engineering productivity, automate workflows, support decision-making, enable summarization, and implement multi-step business processes. The role includes integrating applications with AI services such as LLMs, embeddings, search platforms, and RAG solutions, and supporting applications throughout their operational lifecycle.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical field.
5+ years of software engineering experience.
3+ years of experience developing and supporting production-grade full stack or backend applications using C#, ASP.NET, Angular, REST APIs, and relational or NoSQL databases.
2+ years of experience working with cloud-native technologies, CI/CD pipelines, containerization, and Kubernetes-based deployment environments.
1+ year of hands-on experience designing and implementing AI-enabled solutions, including custom AI agents, prompt engineering, RAG systems, or LLM integrations.
Demonstrated experience designing scalable software architectures and owning applications through design, implementation, deployment, and ongoing operational support.

Nice To Haves

2+ years of experience applying AI-assisted development practices to improve software engineering productivity and reduce development cycles.
Experience designing and implementing custom AI agents using MCP or similar structured agent and tool orchestration frameworks.
Demonstrated success deploying AI-enabled applications in mission-critical or high-availability environments with stringent reliability requirements.
Experience evaluating, refining, and operationalizing AI-generated code and outputs for production use.
Experience building interoperable AI ecosystems that integrate multiple models, tools, APIs, and data sources without tightly coupled architectures.

Responsibilities

Design, develop, test, deploy, and support full stack applications, owning features throughout the entire software development lifecycle.
Build and implement personalized AI assistants that automate workflows, support decision-making, enable summarization, and implement multi-step business processes.
Develop integrations using Model Context Protocol (MCP) or similar frameworks to enable interoperability between AI models, tools, and systems.
Integrate applications with AI services such as LLMs, embeddings, search platforms, and RAG solutions while ensuring security, reliability, scalability, and performance.
Apply AI-assisted development tools to accelerate coding, testing, documentation, and refactoring while maintaining engineering standards and code quality.