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# Senior Software Engineer

- **Company:** Mirantis, Inc.
- **Location:** Raleigh, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Computer Programming, Continuous Integration, Software Design Documents, Distributed Systems, Design of User Interfaces, OpenID, Software Engineering, TypeScript, ReactJS, Claude Code, Kubernetes Helm Charts, Kubernetes, Free and Open-Source Software, Machine Learning Operations, Api Gateway, Model Inference, OpenAI Codex
- **Published:** November 12, 2026
- **Apply:** https://jobs.smartrecruiters.com/Mirantis/744000161110609-senior-software-engineer-

## About the Role

* 5+ years of software engineering experience in infrastructure, platform, or distributed systems.
 * Deep hands-on Kubernetes experience: building and operating production workloads and Helm charts, not just consuming managed clusters.
 * Experience with GPU workloads or LLM inference, or strong adjacent systems experience and a track record of learning fast.
 * Strong Go programming skills; solid CI/CD and infrastructure-as-code skills.
 * Fluency with AI-assisted development tools (Claude Code, OpenAI Codex) as part of your daily engineering workflow.
 * Comfortable with high autonomy on a small, remote-first, written-culture team.

Nice to have

 * Inference performance work (quantization, batching, caching) or distributed serving frameworks.
 * Enterprise deployment experience: air-gapped installs, SSO/OIDC, supply-chain security.
 * UI development experience (e.g. React/TypeScript), useful as the product's management surfaces grow.
 * Open-source contributions in the Kubernetes or ML-infrastructure ecosystems.

## Description

* Design and build LLM serving infrastructure on Kubernetes: deployment, GPU scheduling, scaling, and model lifecycle management.
 * Package the platform for enterprise environments: Helm-based installs, upgrades, and restricted/offline networks.
 * Integrate the serving layer with the platform's API gateway, identity, and metering services.
 * Build the observability for operating GPU inference in production (serving metrics, GPU telemetry).
 * Contribute across a multi-service codebase and help set engineering direction through design docs and reviews.