Senior Software Engineer, AI Infrastructure

Mirantis is building a new enterprise AI infrastructure product that lets organizations run and govern large language models on their own Kubernetes clusters.

You will join a small senior team early, with broad ownership of the model-serving layer and its path to production.

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.

What we're looking for

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.

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.

What does Mirantis offer you?