NetApp

Optimizes cloud infrastructure costs on AWS

Principal Software Engineer

AI Application Engineering +1Updated on Nov 14

Full-timeBellevue, WA, USAIn-person

About the Job

Requirements

At least 12 years of software development experience.
At least 7 years of hands-on experience with fault-tolerant, highly scalable cloud architectures, including service-oriented and cloud-native services such as FaaS and PaaS on AWS, Azure, or GCP.
Strong server-side engineering skills in one or more of Node.js, Python, Java, Go, or Rust.
Experience building RESTful APIs and production microservices backed by SQL and/or NoSQL data stores.
Experience designing distributed systems, cloud-native products, or developer infrastructure and scaling them to production.
Experience building and maintaining CI/CD for large, interconnected deployment pipelines.
Knowledge of cloud security fundamentals, including authentication and authorization (OAuth and SSO), encryption, and compliance.
Ability to make technical decisions under ambiguity, balancing performance, maintainability, cost, and time-to-market and selecting an executable path for the team.
Ability to communicate clearly with executives and engineers in person and in writing, align a team around a design, and write technical documents that settle decisions.
Ability to work effectively across engineering, product, and leadership.
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Responsibilities

Define product architecture, including service boundaries, data models, API contracts, runtime design, and integration patterns connecting AI models to enterprise systems.
Design and build core systems for agent orchestration, knowledge bases and retrieval over enterprise data, tool-calling, multi-cloud execution, and the layers connecting them.
Own the developer-facing APIs, SDKs, and tooling customers build on, ensuring they are fast, reliable, and clear to use.
Lead technical execution across the team by setting engineering standards, running design reviews, unblocking engineers, and maintaining quality while the team ships on schedule.
Mentor engineers and raise the team's technical bar.
Own the architecture, set engineering direction, build production code, and work with leadership to translate product vision into engineering plans the team can ship.

Desired Qualifications

Experience designing or building AI agent systems or LLM-powered products running model inference in production, including tool calling, RAG, and prompt orchestration.
Familiarity with agentic design patterns, including tool-use protocols, context management, multi-step reasoning, and grounding models in live enterprise data.
Experience building developer-facing products, APIs, or SDKs used at scale by external customers.
Experience with containerization and orchestration using Docker and Kubernetes, and infrastructure as code using Terraform or CloudFormation.
Background in enterprise infrastructure, cloud data services, or storage systems, with a working understanding of how enterprise environments operate at scale.
Experience building 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.

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.

Compensation:
The target salary range for this position is 227,800 - 338,800 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU’s), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process.

About the Company

NetApp

Optimizes cloud infrastructure costs on AWS

Spot.io, part of NetApp, helps businesses manage cloud costs and infrastructure on AWS. It uses software that analyzes cloud usage and automates management to lower compute expenses, especially through AWS EC2 spot instances, which offer spare capacity at reduced prices. The product provides deep visibility into cloud spending, an AWS cost optimization calculator for estimating potential savings, and a free action plan tailored to each customer. Revenue comes from selling software licenses and consulting services. Target customers include enterprises using containers and orchestration tools like Kubernetes, EKS, ECS, KOPS, Docker Swarm, and OpenShift. The company aims to reduce cloud compute costs for customers while simplifying cloud operations and improving efficiency.

Company size: 51-200
Company stage: Acquired
Total funding: $53.2M
Headquarters: Tel Aviv-Yafo, Israel
Founded: 2015

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