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Micron Technology

Makes memory and storage chips for AI and PCs

AI Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeSingaporeNo salary listedIn-person

About the Job

Requirements

  • Bachelor’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related technical discipline.
  • Hands-on experience delivering production software applications using Python-based backend technologies and modern software engineering practices.
  • Experience designing, developing, and deploying enterprise-grade Generative AI or Large Language Model solutions.
  • Experience owning the end-to-end software development lifecycle, including solution architecture, development, testing, deployment, and production support.
  • Experience building cloud-native applications in distributed and microservices-based environments.
  • Experience developing AI-powered applications focused on workflow automation, conversational search, document intelligence, or knowledge retrieval.
  • Advanced Python development experience, including building scalable backend services and REST APIs using FastAPI or equivalent frameworks.
  • Hands-on experience with Large Language Models, prompt engineering, model integration, and AI application development.
  • Experience designing and implementing Retrieval-Augmented Generation solutions, vector databases, embeddings, semantic search, and knowledge retrieval systems.
  • Experience developing production-grade AI agent systems using both LangChain and LangGraph.
  • Experience implementing multi-agent architectures, agent orchestration frameworks, tool-calling capabilities, reasoning workflows, and human-in-the-loop AI systems.
  • Experience designing and implementing Model Context Protocol solutions, including MCP servers, MCP clients/hosts, tool registration, runtime tool discovery, and agent integration.
  • Experience integrating AI agents with enterprise APIs, databases, business applications, and external service ecosystems.
  • Experience deploying self-hosted open-source Large Language Models in Kubernetes environments using technologies such as KServe, vLLM, or equivalent model-serving platforms.
  • Experience deploying AI solutions using Kubernetes, Docker, Helm, GitOps, Argo CD, and CI/CD pipelines in production environments.
  • Experience with LLMOps or MLOps practices, including model serving, inference optimization, AI platform operations, and production AI lifecycle management.
  • Experience with distributed systems, asynchronous processing, workflow orchestration platforms, event-driven architectures, and message-queuing technologies.

Responsibilities

  • Design, develop, test, and deploy AI-powered products, applications, and intelligent workflow solutions.
  • Utilize AI-assisted development tools to accelerate software development, solution design, and deployment activities.
  • Support subject matter experts in translating business needs into designs and prototypes.
  • Develop reusable frameworks, services, and components, such as AI Skills, that enable scalable AI adoption across the People Organization.
  • Design and build AI agents capable of making business-context-aware decisions, taking actions across enterprise systems and workflows, and operating autonomously within defined guardrails.
  • Develop multi-agent systems that coordinate work across functions and platforms.
  • Implement agent orchestration, memory, tool integration, and workflow management capabilities.
  • Build AI solutions that integrate and collaborate across multiple enterprise platforms.
  • Develop integrations utilizing APIs, event-driven architectures, and enterprise services.
  • Enable seamless interactions between agents, data sources, and systems to automate end-to-end business processes.
  • Create solutions that leverage enterprise knowledge, workflows, and operational data securely and responsibly.
  • Partner with leaders, process owners, and technology teams to identify AI transformation opportunities.
  • Apply HR domain knowledge to improve recruiting, onboarding, learning, employee services, talent management, workforce planning, and people analytics processes.
  • Drive innovation by rapidly prototyping, testing, and scaling AI solutions that create measurable business value.
  • Ensure solutions comply with enterprise standards for security, privacy, compliance, and responsible AI.
  • Implement monitoring, observability, testing, and evaluation frameworks for AI systems.
  • Support the development of AI governance standards, best practices, and development guidelines.

Desired Qualifications

  • Experience deploying and operating open-source foundation models in enterprise or production environments.
  • Experience with KServe, vLLM, Hugging Face, PyTorch, Temporal, RabbitMQ, Neo4j, or vector database technologies.
  • Experience developing document intelligence, AI-powered document processing, conversational search, or enterprise knowledge management platforms.
  • AWS Certified Developer Associate, Certified Kubernetes Application Developer (CKAD), or similar cloud-native certifications.
  • Experience architecting and deploying AI platforms that support multiple enterprise use cases and business functions.

About the Company

Micron Technology

Makes memory and storage chips for AI and PCs

Micron Technology designs and manufactures memory and storage chips, mainly DRAM and NAND flash, used in data centers, PCs, phones, cars and industrial equipment. It is one of only three companies that make HBM, the stacked high-bandwidth memory placed beside processors in AI servers, and it is the largest memory chipmaker based in the United States. Unlike chip designers that outsource production, Micron runs its own fabs and assembly sites in the United States and across Asia. It earns money by selling chips, memory modules and solid-state drives to cloud providers, device makers and distributors. Micron was founded in 1978 and is headquartered in Boise, Idaho.

Company size
10,001+
Company stage
IPO
Headquarters
Boise, ID
Founded
1978

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