Additionalinformation

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.

We are a Leader for Container Management in G2 (#2 after AWS)!

Companydescription

Company Description

Mirantis, an IREN company, 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. https://www.mirantis.com/

Jobdescription

Job Description

What you'll do

• 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.

Qualifications

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.

• 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.