Software Engineer
Role Overview
NetApp's Chief Platform and Technology Office (CPTO) is hiring AI/ML Engineers to design and build incubation projects that shape NetApp's technology strategy. You will take AI agents, LLM-powered systems, and RAG pipelines from prototype to production. You will also build the React front ends and Python services that put them in users' hands.You bring 2-5 years of hands-on experience deploying AI/ML solutions in production. You have deep expertise in AI agents, LLM integration and optimization, RAG architectures, and modern ML frameworks. You are fluent in Python and comfortable building user-facing applications in React, with Streamlit or Gradio for fast prototypes. Go is a useful addition. Experience in the storage or cloud domain is a strong plus.We value clear communicators who care about responsible AI, quality, and meeting deadlines.
Key Skills for This Role
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Job Summary
NetApp's Chief Platform and Technology Office (CPTO) is hiring AI/ML Engineers to design and build incubation projects that shape NetApp's technology strategy. You will take AI agents, LLM-powered systems, and RAG pipelines from prototype to production. You will also build the React front ends and Python services that put them in users' hands.You bring 2-5 years of hands-on experience deploying AI/ML solutions in production. You have deep expertise in AI agents, LLM integration and optimization, RAG architectures, and modern ML frameworks. You are fluent in Python and comfortable building user-facing applications in React, with Streamlit or Gradio for fast prototypes. Go is a useful addition. Experience in the storage or cloud domain is a strong plus.We value clear communicators who care about responsible AI, quality, and meeting deadlines.
Job Requirements
- Build AI agents that reason, plan, use tools, and execute multi-step tasks.
- Optimize LLM-powered systems, including token optimization, cost-efficient inference, prompt engineering frameworks, and caching.
- Build and scale advanced RAG pipelines with hybrid search, re-ranking, agentic retrieval, and dynamic knowledge base integration.
- Fine-tune and customize foundation models for domain-specific use cases in storage, cloud infrastructure, and enterprise operations.
- Develop and maintain MLOps pipelines for model training, evaluation, deployment, and monitoring at scale.
- Build React front ends for AI products, such as chat and agent interfaces, streaming responses, and dashboards that show agent reasoning, retrieval sources, and evaluation results.
- Develop Python back-end services and APIs that connect the UI to agents, retrieval layers, and model endpoints, and use Streamlit or Gradio to turn ideas into working demos quickly.
- Package and ship full stack applications with Docker and Kubernetes, supported by CI/CD, observability, and automated tests.
- Build fault-tolerant, low-latency distributed systems for real-time AI inference, and explore multi-modal AI, edge inference, and distributed training.
- Contribute to POCs and incubation projects that shape NetApp's AI/ML roadmap, working with engineers, data scientists, and product teams from problem definition through deployment and early customer support.
Education
- 2-5 years of experience deploying AI/ML solutions in production.
- Strong Python skills, including building APIs and back-end services.
- Working experience with React and PythonHands-on experience with AI agents, LLM integration, prompt engineering, and RAG architectures.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, or equivalent experience.
About NetApp
Sells enterprise data storage and cloud management software.
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