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AI Software Engineer: Data Infrastructure

Job in Wichita, Sedgwick County, Kansas, 67232, USA
Listing for: NetApp
Full Time position
Listed on 2026-06-03
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: AI Software Engineer: Intelligent Data Infrastructure

Overview

Title: AI Software Engineer:
Intelligent Data Infrastructure

Location:

San Jose, CA, US, 95128;
Morrisville, NC, US;
Wichita, KS, US, 67208;
Cranberry Township, PA, US, ;
Boulder, CO, US, 80301

Requisition

The Mission:
Power the Next Generation of AI

We are standing at an inflection point. AI is transforming every industry, but beneath every breakthrough model lies a critical foundation that few see and even fewer master: the data infrastructure that makes intelligent systems possible.

These positions require 3 days in office per week in one of the following offices:
Boulder, CO or Pittsburgh, PA or Raleigh, NC or San Jose, CA.

The Office of the Chief Platform and Technology Officer is assembling an elite team of AI Infrastructure Engineers to build the future of intelligent data systems. We don t just store data—we architect the substrate that powers AI factories, from GPU clusters running training workloads to real-time inference pipelines serving billions of requests.

This is not a maintenance role. This is a creation role. You will design the systems that enable enterprises to deploy AI at an unprecedented scale, leveraging Net App s new AI Data Engine (AIDE) and AFX disaggregated storage architecture.

The Opportunity:

Shape what comes next and oin us to solve challenges that exist at the absolute frontier of computer science.

  • Build AI-Native Infrastructure Lead the architecture of next-generation storage systems optimized for AI workloads. Design high-performance data pipelines for massive-scale model training, implement intelligent caching for KV stores, and optimize data planes for GPU clusters. Your work will directly accelerate how quickly organizations can move from data to deployed intelligence.
  • Pioneer Forward-Looking Research Work at the intersection of distributed systems, AI, and storage. Investigate novel approaches to scalable AI inferencing systems, semantic data discovery, and data curation systems. Turn proof-of-concepts into production systems that redefine industry standards.
  • Amplify Your Impact with AI We don t just build AI—we use it. Leverage Cursor, Claude Code, and emerging AI development tools to accelerate your workflow, automate repetitive tasks, and focus on solving problems that matter. You ll operate at the cutting edge of  vibe coding  while maintaining the rigor of production-grade engineering.

What You ll Bring

You are a generalist with depth—someone who moves fluidly between AI technologies and distributed system architectures, who gets energy from ambiguous problems, and who possesses what we call  fearless curiosity .

You thrive when:

  • Ownership is total:
    You own problems end-to-end, from architecture to production operations, and take pride in systems that run flawlessly at scale
  • Change is constant:
    You view rapid technological shifts as opportunities to add structure and clarity, not as obstacles
  • Learning is relentless:
    You have a rich life of  side quests —self-driven projects that demonstrate your curiosity beyond your day job.
  • AI is a multiplier:
    You view AI coding assistants and generative tools as force multipliers that let you tackle complexity that was previously impossible

You bring:

  • Deep systems expertise:
    Mastery of Golang, Python, and C/C++, with an intuitive understanding of file systems, advanced data structures, and algorithms. You understand that storage isn t just about bits on disk—it's about enabling the next wave of intelligent applications
  • AI infrastructure fluency:
    Deep knowledge of AI Infra:
    Kubernetes, operating systems, Storage systems and distributed systems.
  • Quantitative intuition:
    The ability to build simplified performance models, identify bottlenecks through deep analysis, and design for scalability from first principles
  • Growth mindset:
    For yourself, your team, and the organization. You balance optimism with realism, make smart bets, and understand that some experiments will fail fast while others will drive the company forward

What You'll Create

  • AI Data Architectures:
    Design storage and networking systems that connect structured and unstructured data to LLMs with unprecedented performance, enabling real-time inference and massive-scale…
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