Principal Software Engineer

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. They are hiring a Principal Engineer to be the technical anchor for this product, responsible for owning the architecture, setting the engineering direction, and building alongside the team.

Responsibilities:

• 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

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