Senior Software Engineer, AI Infrastructure

🔥 12 hours ago

🌐 Kazakhstan, United States – Remote

🇰🇿 Kazakhstan – Remote 🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Mirantis

WebsiteLinkedInAll Job Openings

501 - 1000 employees

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Mirantis is a company that specializes in container management and cloud infrastructure solutions. It offers a range of products, including Mirantis Kubernetes Engine (MKE), Mirantis OpenStack for Kubernetes (MOSK), and Mirantis Container Cloud (MCC), which provide enterprise-level Kubernetes and container management platforms. Mirantis also develops tools for secure software supply chains, such as the Mirantis Container Runtime (MCR) and Mirantis Secure Registry (MSR). As an advocate for open source technologies, Mirantis supports various projects and provides resources like Lens Desktop, a popular Kubernetes IDE, and technical support for enterprises adopting cloud-native technologies. Their solutions cater to sectors such as public services, financial services, and broader SaaS and technology services industries.

📋 Description

• Design and build LLM serving infrastructure on Kubernetes, including deployment, GPU scheduling, scaling, and model lifecycle management • Package the platform for enterprise environments through Helm-based installs, upgrades, and restricted/offline networks • Integrate the serving layer with the platform’s API gateway, identity, and metering services • Build observability for operating GPU inference in production, including serving metrics and GPU telemetry • Contribute across a multi-service codebase • Help set engineering direction through design documents and code reviews • Join a small senior team with broad ownership of the model-serving layer and its path to production

🎯 Requirements

• 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 • 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, including Claude Code and OpenAI Codex, as part of daily engineering workflow • Comfortable with high autonomy on a small, remote-first, written-culture team • Nice to have: inference performance work such as quantization, batching, or caching • Nice to have: distributed serving frameworks • Nice to have: enterprise deployment experience including air-gapped installs, SSO/OIDC, and supply-chain security • Nice to have: UI development experience such as React/TypeScript • Nice to have: open-source contributions in Kubernetes or ML-infrastructure ecosystems

🏖️ Benefits

• Professional development and training • Attend conferences and working groups • Company outings, happy hours, hackathons, and tech talks • Competitive compensation package with a strong benefits plan • Remote work arrangement