Senior Software Engineer, UI

Mirantis•Raleigh, NC

About The Position

The Enterprise UI team owns the consoles for Mirantis Kubernetes Engine (MKE) and a new enterprise AI infrastructure product for running and governing large language models. The role joins a small senior team with broad ownership across established and new product surfaces. The engineer will build and evolve management consoles for cluster, node, and workload management, as well as AI product capabilities including model deployment, inference endpoints, GPU capacity, quotas, API keys, and usage. The work includes turning operational data—such as cluster health, serving metrics, GPU telemetry, and cost and metering information—into trustworthy interfaces, including clear handling of workloads that are still scheduling or have failed. The role owns and extends a shared design system and component library, integrates with platform APIs, and collaborates with backend engineers to shape APIs before they are finalized. It also involves shipping UI into enterprise environments through Helm-packaged delivery, versioned upgrades, and restricted or offline networks without runtime dependency on the public internet. The engineer balances new product development with mature-product release cycles, upgrades for existing customers, and bug triage. They contribute across a multi-service codebase and help set engineering direction through design documents and reviews.

Requirements

At least 5 years of experience building production web applications.
Strong depth in React and TypeScript.
Strong command of modern React and server rendering.
Ability to reason about Next.js App Router, Server Components, and Server Actions, including what belongs on the server and its security and latency implications.
Experience building data-dense operational interfaces with large tables, filtering, charts, and live-updating state.
Ability to handle loading, partial, and error states deliberately.
Fluency in CSS and token-driven styling.
Ability to work with a design system rather than around it.
Treat accessibility and testing as part of the definition of done.
Experience with testing tools such as Vitest, Testing Library, and Playwright.
Fluency with AI-assisted development tools such as Claude Code and OpenAI Codex as part of the daily engineering workflow.
Comfort working with high autonomy on a small, remote-first team with a written culture.

Nice To Haves

Kubernetes or infrastructure-tooling UI experience.
Comfort reading Go services and Kubernetes APIs to answer questions independently.
Experience with AI product surfaces such as model catalogs, playgrounds, prompt and token usage reporting, or streaming responses.
Ownership of a design system or component library used by more than one application.
Enterprise deployment experience, including air-gapped installs, SSO/OIDC, RBAC-driven interfaces, or FIPS or STIG compliance.
Experience with frontend observability and product analytics tools such as Sentry, OpenTelemetry, or PostHog.
Open-source contributions in the Kubernetes or machine learning ecosystems.

Responsibilities

Build and evolve management consoles for cluster, node, and workload management in MKE.
Build AI product interfaces for model deployment, inference endpoints, GPU capacity, quotas, API keys, and usage.
Create trustworthy interfaces for operational data, including cluster health, serving metrics, GPU telemetry, and cost and metering views.
Handle loading, partial, scheduling, and error states deliberately in operational interfaces.
Own and extend a shared design system and component library for reuse across products.
Integrate with Kubernetes, API gateway, identity, and metering platform APIs.
Collaborate with backend engineers to shape APIs before they harden and identify API designs that would create poor user experiences.
Ship UI into enterprise environments using Helm-packaged delivery and versioned upgrades, including restricted or offline networks.
Balance new product development with release cycles, upgrades for existing customers, and bug triage.
Contribute across a multi-service codebase and help set engineering direction through design documents and reviews.