Principal Engineer, AI BU

As a Principal Engineer in NetApps AI BU you are 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 are the engineer other teams turn to for the hardest design and architecture problems and you drive outcomes through technical depth and influence rather than management authority retaining a hands-on individual-contributor focus.

As a Principal Engineer you will:

• 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 authoring design docs/RFCs that align stakeholders across teams.
• Stay hands-on: write production code review the highest stakes designs and PRs and personally unblock the hardest engineering problems.
• Partner with engineering and product leadership to translate business priorities into technical roadmaps and architecture decisions.
• Mentor and raise the technical bar for engineers across teams without formal management authority over them.
• Identify systemic technical risk architectural debt scalability bottlenecks reliability gaps and drive it to resolution before it becomes a team-level fire.
• 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 across the teams you influence.
• Evaluate and introduce new technologies frameworks and architectural patterns balancing innovation with pragmatism.

• 12 years of hands-on software engineering experience including designing and building large-scale distributed systems.
• Demonstrated track record as technical lead or architect on multi-team or org-wide initiatives.
• Deep hands-on experience with cloud-native architectures on AWS Azure or Google Cloud.
• Well versed in using agentic engineering using local and/or frontier models.
• Hands-on experience with Distributed Storage Systems.
• Proven ability to build technical consensus and influence engineering direction across teams without formal authority.
• Strong system design skills with direct ownership of architecture for highly available low-latency large-scale services.
• Excellent written and verbal communication skills able to author design docs/RFCs and present technical trade-offs to engineers and executives alike.
• Experience with data processing analytics and AI/ML systems.
• Track record of mentoring engineers and raising the technical quality bar across teams.
• Prior experience building CI/CD infrastructure for large-scale deployments.

Preferred Qualifications

• Domain expertise on 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.