Micron is a global leader in memory and storage, powering AI and compute-intensive applications from cloud to edge with innovative semiconductor solutions.
About the role
AI Solution Development: Build and deploy AI-driven tools and workflows using platforms like Copilot Studio , UiPath , and other automation frameworks. Integration & Enablement: Connect AI agents with enterprise systems (e.g., SharePoint, M365), external APIs, knowledge bases, and ensure seamless interoperability. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor’s or master’s degree in computer science, AI, Machine Learning, Data Science or related field
- Professionals with a minimum of 5 years of experience in software development, including at least 2 years specializing in AI/ML engineering
- Strong understanding of AI concepts , machine learning pipelines , and automation tools
- Hands-on experience or coursework in Copilot Studio , UiPath , and SharePoint
- Knowledge with cloud AI platforms: Azure AI Foundry, AWS Bedrock, and/or Google Vertex AI
- Knowledge with scalable context management solutions including retrieval-augmented generation (RAG ), semantic chunking, and memory persistence for long-horizon tasks
More about this role
Our vision is to transform how the world uses information to enrich life for all .
Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.
Join Micron’s AI Enablement team and help accelerate enterprise-wide AI adoption. This role is designed for engineers passionate about applying AI to real-world business challenges. You will work on rapid prototyping, automation, and integration of AI solutions that enhance productivity and innovation across diverse business areas.
AI Solution Development: Build and deploy AI-driven tools and workflows using platforms like Copilot Studio , UiPath , and other automation frameworks.
Integration & Enablement: Connect AI agents with enterprise systems (e.g., SharePoint, M365), external APIs, knowledge bases, and ensure seamless interoperability.
Process Automation: Identify repetitive tasks and design intelligent automation solutions to improve efficiency.
Collaboration & Training: Partner with cross-functional teams to enable AI literacy, create best-practice documentation, and support...
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