Principal Software Engineer

About the role

NetApp's Cloud AI team is building an enterprise AI agent platform that helps Fortune 500 companies automate complex workflows on their own data, across on-premises and multi-cloud environments. It brings together large language models, agentic frameworks, and production cloud engineering.
We are hiring a Principal Engineer to be the technical anchor for this product. You will own the architecture, set the engineering direction, and build alongside the team. This is a hands-on role: you will design the core systems and write the production code behind them, while working with leadership to turn product vision into engineering plans the team can ship.

What you will build

• Define the product architecture: service boundaries, data models, API contracts, runtime design, and the integration patterns that connect AI models to enterprise systems.
• Design and build the core systems: agent orchestration, knowledge bases and retrieval over enterprise data, tool-calling, multi-cloud execution, and the layers that tie them together.
• Own the developer-facing surface: the APIs, SDKs, and tooling that customers build on. It has to be fast, reliable, and clear to work with.
• Lead technical execution across the team: set engineering standards, run design reviews, unblock engineers, and hold the quality bar while the team ships on schedule.
• Mentor engineers and raise the technical bar of the team.

Experience Requirements

• 12+ years in software development.
• 7+ years hands-on with fault-tolerant, highly scalable cloud architectures, including service-oriented and cloud-native services (FaaS, PaaS) on at least one hyperscaler (AWS, Azure, or GCP).

Required Qualifications

• Strong server-side engineering in one or more of Node.js, Python, Java, Go, or Rust. Front-end experience (TypeScript, React or Angular) is a plus.
• Built RESTful APIs and microservices in production, backed by SQL and/or NoSQL data stores.
• Designed distributed systems, cloud-native products, or developer infrastructure and scaled them to production.
• Built and maintained CI/CD for large, interconnected deployment pipelines.
• Applied cloud security fundamentals: authentication and authorization (OAuth, SSO), encryption, and compliance.
• Made high-quality technical decisions under ambiguity, trading off performance, maintainability, cost, and time-to-market, and choosing a path the team can execute.
• Communicate clearly with executives and engineers, in person and in writing. You can align a team around a design and write technical documents that settle decisions.
• Work effectively across engineering, product, and leadership.

Preferred Qualifications

• Designed or built AI agent systems or LLM-powered products that run model inference in production: tool calling, RAG, prompt orchestration.
• Deep familiarity with agentic design patterns: tool-use protocols, context management, multi-step reasoning, and grounding models in live enterprise data.
• Built developer-facing products, APIs, or SDKs used by external customers at scale.
• Containerization and orchestration (Docker, Kubernetes) and infrastructure as code (Terraform, CloudFormation).
• Background in enterprise infrastructure, cloud data services, or storage systems, with a working understanding of how enterprise environments run at scale.
• Built a new product end-to-end inside a larger company.
• Prior experience as a principal engineer or technical lead in a high-performance engineering organization.

Education

• Bachelor's degree in Computer Science, Engineering, or related field; or equivalent practical experience.