Principal Engineer, AI BU

NetApp•San Jose, NC

About The Position

As a Principal Engineer in NetApp's AI BU, you will serve as a senior technical authority, architecting and tech-leading complex, cross-team initiatives and setting technical direction for products at the intersection of storage, data, and AI. You will address the hardest design and architecture problems and drive outcomes through technical depth and influence rather than management authority. The role remains hands-on and focused on individual contribution. You will own end-to-end system design for major AI BU initiatives, set technical direction and design standards across engineering teams, and guide ambiguous, cross-cutting problems toward well-reasoned solutions. The position combines production coding and high-stakes design and code reviews with partnership across engineering and product leadership, mentoring, risk reduction, and representation in cross-functional and executive technical reviews. You will also champion engineering best practices and evaluate new technologies and architectural patterns.

Requirements

12+ years of hands-on software engineering experience, including designing and building large-scale distributed systems.
Demonstrated track record as a technical lead or architect on multi-team or organization-wide initiatives.
Deep hands-on experience with cloud-native architectures on AWS, Azure, or Google Cloud.
Experience using agentic engineering with local and/or frontier models.
Hands-on experience with distributed storage systems.
Ability to build technical consensus and influence engineering direction across teams without formal authority.
Strong system design skills and direct ownership of architecture for highly available, low-latency, large-scale services.
Excellent written and verbal communication skills, including authoring design documents or RFCs and presenting technical trade-offs to engineers and executives.
Experience with data processing, analytics, and AI/ML systems.
Track record of mentoring engineers and raising technical quality across teams.
Prior experience building CI/CD infrastructure for large-scale deployments.

Nice To Haves

Domain expertise in knowledge graphs, semantics, and data modeling.
Hands-on experience with distributed database systems.
Hands-on experience with training and deploying AI models.
Hands-on experience with GPU workloads and accelerated computing infrastructure.
Master’s degree; equivalent practical experience is also accepted.

Responsibilities

Serve as technical architect and/or tech lead across one or more major AI BU initiatives, owning system design end-to-end.
Set technical direction and design standards across multiple engineering teams, ensuring architectural coherence.
Drive ambiguous, cross-cutting technical problems to well-reasoned solutions and author design documents or RFCs to align stakeholders.
Write production code, review high-stakes designs and pull requests, and personally unblock difficult engineering problems.
Partner with engineering and product leadership to translate business priorities into technical roadmaps and architecture decisions.
Mentor engineers and raise the technical bar across teams without formal management authority.
Identify systemic technical risks, including architectural debt, scalability bottlenecks, and reliability gaps, and drive them to resolution.
Represent AI BU engineering in cross-functional and executive technical reviews, articulating trade-offs and recommendations.
Champion best practices in system design, testing, observability, and operational excellence.
Evaluate and introduce technologies, frameworks, and architectural patterns while balancing innovation with pragmatism.