Senior Software Engineer (Storage) – remote in the US

Remote from: USA
Annual salary: Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Department: Software Engineering
Employment type: Full Time,
Job posted: 24 Jul 2026
Apply before: 24 Aug 2026
Experience level: Senior
Views / Applies: 36 / 3

Build AI Infrastructure Your Way, Anywhere.

Computer Software
1999

AI Summary

Mirantis is seeking a Senior Software Engineer (Storage) to design and build software for provisioning, integrating, and operating high-performance storage for GPU-accelerated compute and AI platforms. The role involves developing control-plane services, CSI drivers, and tooling connecting enterprise storage systems to Kubernetes-based workloads. Candidates should have 5+ years in Go, deep storage systems expertise, and experience with Kubernetes storage and infrastructure-as-code. The position is remote within the US and focuses on hybrid, edge, and air-gapped deployments using the Mirantis K0rdent stack. This is a high-impact role requiring self-direction, strong communication, and end-to-end ownership of ambiguous problems.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight The role requires deep expertise in storage systems, Go, and Kubernetes, plus the ability to own complex ambiguous problems end-to-end, making it challenging but not extreme.

Salary Analysis

AI Insight The job listing does not specify a salary, but based on market data for senior software engineers specializing in storage and Kubernetes in the US, the typical range is $130k-$200k. The median of $165k is competitive for a remote role at a company like Mirantis, which values deep technical expertise and autonomy.

Core Skills Required

Go Kubernetes Storage Systems CSI Terraform GitOps AI Infrastructure Distributed Systems Infrastructure as Code Cluster API

Cover Letter Sample

I am excited to apply for the Senior Software Engineer (Storage) position at Mirantis. With over five years of experience building production-grade storage systems in Go and integrating them with Kubernetes, I have a strong track record of delivering reliable, high-performance data paths for AI and compute workloads.

Your focus on GPU-accelerated infrastructure and the K0rdent stack aligns perfectly with my background in developing CSI drivers, Terraform modules, and GitOps pipelines for scale-out storage platforms like Dell PowerScale and VAST.

I thrive in self-directed roles where I can own ambiguous problems end-to-end, and I am confident in my ability to contribute to your mission of enabling sovereign AI infrastructure.

I look forward to discussing how my technical depth and operational rigor can support Mirantis’s innovative work in Kubernetes-native AI.

Sample Interview Questions

Can you walk us through a time when you designed a storage solution for a high-throughput workload? What were the key challenges and how did you address them?

In my previous role, I built a CSI driver for a distributed storage system to support AI training pipelines. The main challenge was achieving low latency while handling large sequential reads. I implemented caching layers and tuned the I/O scheduler, and used profiling to identify bottlenecks. The solution reduced latency by 30% and met throughput requirements.

How do you ensure the reliability and consistency of storage operations in a Kubernetes environment?

I rely on declarative automation with operators and controllers. For consistency, I use idempotent operations and comprehensive testing, including chaos engineering. I also implement monitoring and alerting for storage health, and design for graceful failure handling using retry logic and state machines.

Explain your experience with Go for building control-plane services. How do you structure code for testability and maintainability?

I use clean architecture patterns: separate interfaces for storage backends, dependency injection, and extensive unit tests. I follow Go conventions like small interfaces, use of contexts for cancellation, and error wrapping. For maintainability, I enforce code reviews and use linters.

Describe a time you had to optimize storage performance for AI/ML workloads. What metrics did you focus on and what changes did you make?

For a GPU cluster, I focused on data throughput and GPU direct storage access. I tuned filesystem parameters, implemented parallel data loading, and used GPUDirect Storage to bypass CPU. I monitored IOPS and latency, and the changes improved training speed by 40%.

How would you approach integrating a new enterprise storage system (e.g., Dell PowerScale) into an existing Kubernetes-based platform?

I would start by understanding the storage system's API and performance characteristics. Then I'd develop a CSI driver and Terraform provider for provisioning. I'd test with realistic workloads, ensure it meets SLAs, and integrate monitoring. The code would be modular to support other storage backends.

Company Description

About Mirantis

Mirantis is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications. By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environment—on-premises, in the cloud, at the edge, or in sovereign data centers. As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility. Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy.

Job Description

Overview

Design and build the software that provisions, integrates, and operates high-performance storage for GPU-accelerated compute and AI platforms. You will develop the control-plane services, drivers, and tooling that connect enterprise and scale-out storage systems to Kubernetes-based workloads across hybrid, edge, and air-gapped deployments built on the Mirantis K0rdent stack.

About the Role

We are looking for a software engineer who thinks in systems and data paths — someone who can reason about throughput, latency, consistency, and failure across a storage stack, then express that understanding as clean, testable Go. The right candidate has built production software against real storage systems (whether enterprise NAS, scale-out, or object), understands what makes storage fast and reliable at scale, and prefers declarative automation over manual operations. You should be self-directed, comfortable owning ambiguous problems end to end, and effective communicating technical decisions across teams.

Responsibilities

1. Storage Software & Integration

Design and build control-plane services, drivers (e.g., CSI), and tooling that provision, configure, and operate storage for Kubernetes-based AI/compute workloads.
Integrate high-performance storage platforms — Dell PowerScale, VAST, and comparable systems — into automated, declarative provisioning workflows.
Build data-path, telemetry, and observability tooling to diagnose and resolve performance, reliability, and scaling issues.

2. Software & Automation

Write production-quality software — primarily in Go — with strong testing, code review, and operational rigor.
Deliver infrastructure-as-code (Terraform/OpenTofu) and GitOps-driven pipelines (ArgoCD or Flux) for storage configuration and lifecycle.
Support bare-metal and hybrid provisioning where storage intersects host and cluster bring-up.

3. Platform & Hybrid Delivery

Deliver storage integration for k0s-based Kubernetes via Cluster API (CAPI) and K0rdent management/child cluster topologies.
Architect storage software for fully disconnected (air-gapped) environments, including local artifact/mirror connectivity (Harbor) and PKI/TLS considerations.

Qualifications

5+ years of software development, including production systems, with Go as a primary language.
5+ years building or integrating storage systems (distributed, scale-out, NAS, or object) at scale.
Hands-on experience with high-performance storage platforms such as Dell PowerScale, VAST, or comparable technologies.
Solid understanding of storage fundamentals: file/block/object models, throughput and latency behavior, caching, consistency, and failure modes.
Experience with Kubernetes storage (CSI, persistent volumes, storage classes) and infrastructure-as-code.
Strong written and verbal communication with technical audiences.

Preferred

Proficiency in Python and/or Rust in addition to Go.
Experience with the Mirantis K0rdent stack (K0rdent Enterprise, K0rdent AI, k0s, MKE) and Cluster API.
Experience developing storage for GPU/AI workloads (high-throughput data pipelines, GPUDirect Storage).
Proven experience in sovereign or high-security air-gapped environments.

Additional Information

What does Mirantis offer you?
– Work with an established Silicon Valley leader in the cloud infrastructure industry;
– Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies;
– Be a part of cutting-edge, open-source innovation;
– Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued;
– Professional development and training;
– Attend conferences and working groups;
– Company outings, happy hours, hackathons, and tech talks;
– Receive a competitive compensation package with a strong benefits plan.

It is understood that Mirantis, Inc. may use automated decision-making technology (ADMT) for specific employment-related decisions. Opting out of ADMT use is requested for decisions about evaluation and review connected with the specific employment decision for the position applied for. You also have the right to appeal any decisions made by ADMT by sending your request to isamoylova@mirantis.com
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