Member of Technical Staff, Agentic AI Architect

Micron•Boise, ID

20h

About The Position

Micron Technology’s Smart Manufacturing and AI team is seeking an engineer to develop production-grade Agentic AI solutions for manufacturing processes and systems. The role combines applied Agentic AI engineering with production systems work: architecting autonomous agents and the data and agentic pipelines that power them, deploying agents to Kubernetes and containerized cloud environments, and profiling and evaluating agent performance to deliver measurable manufacturing impact. The position collaborates with Data Scientists, Data Engineers, and expert users to build scalable solutions that generate value and insight from Micron’s manufacturing data and systems.

Requirements

Bachelor’s or Master’s degree in Computer Science, Statistics, or a related technical field; a Ph.D. is a plus.
Experience optimizing inference engines such as vLLM or TensorRT-LLM for autonomous AI agent and LLM workloads.
Experience developing GenAI applications and AI agents using one or more frameworks.
Proficiency with LLMs, including prompt engineering, function calling/tool use, and Chain-of-Thought reasoning.
Experience designing and implementing RAG pipelines, including document ingestion, chunking, embeddings, and vector search.
Experience building and operating end-to-end systems that automate testing, evaluation, and deployment of autonomous AI agents.
Familiarity with MCP tools, plugins, and skills, and the A2A protocol for interoperable multi-agent systems.
Understanding of AI agent security practices, including sandboxing, access control, and mitigating prompt-injection and tool-misuse risks.
Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
Strong scripting, programming, and software development skills, and a desire to work in a cloud environment.
At least 8 years of relevant industry experience spanning large-scale data/ML pipelines and/or production Agentic AI systems.
Outstanding analytical thinking, interpersonal, oral, and written communication skills.
Ability to prioritize and meet critical project timelines in a fast-paced environment.
Experience with Kubernetes for orchestrating containerized applications, including deployment and scaling of AI agent workloads.

Nice To Haves

Experience designing and coordinating multi-agent systems, including collaboration between specialized agents.
Experience designing and operating agent swarms for distributed, parallelized task execution.
Experience with agent profiling and evaluation tools to identify performance regressions and bottlenecks across agent pipelines.
Hands-on experience with LangChain, LangGraph, or CrewAI.
Proficiency in TypeScript and/or Rust.
Demonstrated ability to study and transform data science prototypes into production solutions.
Knowledge of computer vision and/or signal processing, including classification and feature-extraction techniques.
Experience with Microsoft Agent Framework or Google Agent Development Kit.
Ph.D. in a related technical field.

Responsibilities

Design and develop autonomous AI agents capable of multi-step reasoning, planning, and tool execution to automate complex manufacturing workflows.
Implement agentic frameworks that orchestrate LLM interactions with internal APIs, databases, and software tools.
Build and maintain agent evaluation harnesses to benchmark accuracy, reliability, and task success across complex workflows.
Analyze and profile agent and inference workloads to identify and resolve compute and latency bottlenecks, using observability and profiling tools such as PyTorch Profiler, LangSmith, and OpenTelemetry.
Implement interoperable multi-agent systems using the Agent-to-Agent (A2A) protocol and Model Context Protocol (MCP), including MCP tools, plugins, and skills.
Create and maintain CI/CD pipelines for deploying AI agents to Kubernetes and containerized cloud environments.
Design and implement security controls for autonomous agents, including sandboxing, access control, and mitigation of prompt-injection and tool-misuse risks.
Mentor engineers on agentic system design paradigms and optimization techniques.