AI Full Stack Engineer

Description

The company is a semiconductor leader that makes memory and storage products.

The team builds and maintains internal software that improves engineering productivity and supports smarter business workflows. It works with modern full stack tools, cloud-native platforms and AI-driven development methods to ship scalable, secure, dependable applications for core operations.

This is an AI Full Stack Engineer role building and running applications where AI is central. The work combines full stack engineering with AI-native practices such as custom agents, prompt design, MCP integrations and AI-assisted delivery, aimed at faster development and better business results.

Responsibilities

• Own features across the whole software lifecycle, from design and build through testing, deployment and support of full stack applications.
• Create personalized AI assistants that automate workflows, aid decisions, summarize content and carry out multi-step business processes.
• Build integrations with Model Context Protocol (MCP) or comparable frameworks so AI models, tools and systems can work together.
• Connect applications to AI services such as LLMs, embeddings, search platforms and RAG solutions, keeping them secure, reliable, scalable and fast.
• Use AI-assisted tools to speed up coding, testing, documentation and refactoring without lowering engineering standards or code quality.

Requirements

• Minimum qualifications: a bachelor's degree in computer science, software engineering, information technology or a related technical field, plus 5+ years of software engineering experience.
• Minimum: 3+ years building and supporting production full stack or backend applications with C, ASP.NET, Angular, REST APIs and relational or NoSQL databases.
• Minimum: 2+ years working with cloud-native technology, CI/CD pipelines, containers and Kubernetes-based deployments.
• Minimum: 1+ year of hands-on work designing and implementing AI-enabled solutions, such as custom AI agents, prompt engineering, RAG systems or LLM integrations.
• Minimum: proven experience designing scalable architectures and owning applications from design through deployment and ongoing operational support.
• Preferred qualifications: 2+ years applying AI-assisted development to raise engineering productivity and shorten development cycles.
• Preferred: experience designing custom AI agents with MCP or similar structured agent and tool orchestration frameworks.
• Preferred: a record of deploying AI-enabled applications in mission-critical or high-availability settings with strict reliability requirements.
• Preferred: experience assessing, refining and putting AI-generated code and outputs into production.
• Preferred: experience building interoperable AI ecosystems that connect multiple models, tools, APIs and data sources without tight coupling.

Conditions

Right to work: review the right-to-work information linked from the careers site.

The company prohibits child labor, follows applicable labor laws and standards, and never charges candidates recruitment fees.

Benefits

• A choice of medical, dental and vision plans in all locations, so you can pick the coverage that fits your family and budget.
• Income protection if illness or injury keeps you from working.
• Paid family leave.
• A paid time-off program and paid holidays.
• Full benefit details are in the Benefits Guide on the careers site.