Software Engineer - AI Platforms (GenAI & Agentic Systems)

Overview

At NetApp, we have a history of helping customers turn challenges into business opportunities. That’s because we bring new thinking to age-old problems, like how to use data most effectively in the most efficient possible way. As an Engineer with NetApp, you’ll have the opportunity to work with modern cloud and container orchestration technologies in a production setting. You’ll play an important role in scaling systems sustainably through automation and evolving them by pushing for changes to improve reliability and velocity.

Own Every Moment at NetApp

At NetApp, your ideas power innovation. We lead in intelligent data infrastructure—delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud.

Ready to innovate and contribute to our path to $10B? Here, you’ll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you’re ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Join teams that drive results, innovate to elevate, and excel together across every function.

Job Summary

NetApp is seeking a highly motivated and innovative AI Engineer to join our growing AI and Automation team. In this role, you will contribute to the design, development, and deployment of next-generation Agentic AI applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern orchestration frameworks. You will collaborate with cross-functional teams to build scalable AI solutions that solve real-world business challenges while driving innovation across the organization.

Job Requirements

• Design, develop, and maintain Agentic AI applications using modern AI frameworks such as LangGraph, LangChain, Google ADK, Phoenix, Guardrails, Mem0, and related technologies.
• Develop scalable Python-based solutions for agent orchestration, workflow automation, data processing, API integrations, and AI-driven applications.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines, vector search capabilities, prompt engineering frameworks, and memory management systems.
• Leverage Large Language Models (LLMs), vector databases, and semantic search technologies to deliver robust and accurate AI solutions.
• Evaluate, prototype, and integrate emerging AI technologies, including Model Context Protocol (MCP), Agent-to-Agent (A2A) communication, and related advancements in the Generative AI ecosystem.
• Collaborate with cross-functional teams to design, develop, and deliver innovative AI-powered products and features.
• Perform experimentation, testing, performance optimization, and debugging of AI applications to ensure scalability, reliability, and accuracy.
• software engineering best practices, including code reviews, testing, documentation, and continuous improvement.
• Demonstrate strong proficiency in Python, including object-oriented programming and experience with libraries and frameworks such as NumPy, Pandas, FastAPI, and Streamlit.
• Possess hands-on experience working with LLM APIs, Agentic AI frameworks, and Generative AI application development.
• Have exposure to vector databases and AI tools such as FAISS, Milvus, Hugging Face, or similar technologies.
• Exhibit strong analytical, problem-solving, and communication skills with the ability to work effectively in a fast-paced, collaborative environment.

Education

• Typically requires a minimum of 4- 8 years of related experience.
• Bachelor’s degree in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Information Technology, or a related technical field; or equivalent work experience.
• Experience building enterprise software applications with a strong focus on Python development and Generative AI technologies.
• Proven experience developing AI solutions leveraging Large Language Models (LLMs), Agentic AI frameworks, Retrieval-Augmented Generation (RAG), and modern AI orchestration patterns.
• A Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field is a plus.

At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared durin…