Staff AI Engineer

Staff AI Engineer

at Micron (Boise, ID, onsite) to build modern AI-first full stack applications and production systems, with a focus on custom AI agents, MCP, and operationalizing AI for manufacturing.

Responsibilities

Own features end-to-end across system design, implementation, testing, observability, deployment, and lifecycle support

Support platform enablement and architecture decisions through code reviews and shared engineering standards

Design, build, test, deploy, and operate full stack software solutions

Collaborate with business teams to translate requirements into scalable solutions

Build and implement

Custom AI Agents

for workflows such as task automation, decision support, summarization, multi-step reasoning, and guided execution

Demonstrate engineering proficiency using

Vibe Coding

prototypes in a timely development process

Integrate systems using

Model Context Protocol (MCP)

to enable structured context sharing between models, tools, and agents

Expose tools and capabilities to LLM-based agents and enable interoperability across AI components without hard-coded integrations

Integrate applications with external and internal AI services including

LLMs , embeddings, search, and tools via well-designed APIs

Harden AI components for 24x7 critical physical manufacturing systems with focus on reliability, resiliency, latency, performance, security, permissions, data boundaries, observability, and maintainability

Apply

retrieval-augmented generation (RAG)

systems within production environments

Use AI-assisted development tools (code generation, refactoring, test creation, documentation), and critically evaluate and refine AI-generated output with human judgment

Conduct requirements gathering and analysis for software domains, interfaces, and characteristics

Write code using programming, scripting, and database languages; support testing, deployment, maintenance, and evolution

Follow guidelines for coding standards, code reviews, source control, build processes, testing, and operations

Requirements

Strong full stack software engineering foundation including object-oriented design, clean code, testing strategies, and long-term maintainability

Experience building and operating production-grade backend or full-stack systems, including API design, service integration, and data persistence

Ability to design and evolve scalable system architectures with tradeoffs across performance, reliability, security, and developer productivity

Experience in cloud-native environments including

CI/CD

pipelines, containerized deployments, and modern operational practices

Solid understanding of data modeling and storage across relational and non-relational technologies, including selecting the right tool

Track record of owning software end-to-end from design through lifecycle support, collaborating across engineering and business teams

Experience with

C# ,

ASP.NET ,

Angular ,

RESTful APIs ,

SQL

and

NoSQL

databases, and

Kubernetes -based platforms

Experience designing and implementing custom AI agents beyond simple chat interfaces

AI-native skills including

prompt engineering ,

Vibe Coding , context window management, and

chain-of-thought design

Experience integrating systems using

MCP

or equivalent structured agent/tool interfaces, including prompt design and tool invocation

Ability to reason about hallucination risk, failure modes, permissions, and guardrails in AI-enabled systems, plus hands-on RAG integration experience

Preferred Qualifications

Experience applying AI-enabled development practices to accelerate engineering workflows and improve productivity

Ability to critically evaluate AI-generated outputs and refine them for production-grade systems

Experience building interoperable AI systems without hard-coded integrations

Strong understanding of operationalizing AI in critical environments with high reliability and performance requirements

Kubernetes / Platform Engineering

Strong interest in Kubernetes and cloud-native infrastructure, including running, upgrading, and troubleshooting production clusters

Desire to deepen expertise in container orchestration, GPU workloads, and platform reliability

Experience designing and running distributed systems on Kubernetes

Understanding of message-driven architectures, horizontal scaling, fault tolerance, and multi-tenant workloads

Help shape a platform roadmap for processing large volumes of data across sites

Technologies

C#, ASP.NET, Angular

RESTful APIs

SQL, NoSQL

Kubernetes

CI/CD pipelines, containerized deployments

Model Context Protocol (MCP)

LLMs, embeddings, search

Retrieval-augmented generation (RAG)

Prompt engineering, Vibe Coding, context window management, chain-of-thought design

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