Senior Software Engineer, AI Infrastructure

Mirantis

. Design and build LLM serving infrastructure on Kubernetes .

Posted 10/6/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building LLM serving infrastructure on Kubernetes, with strong capabilities in GPU scheduling, model lifecycle management, and enterprise deployment. Proficient in Go programming and CI/CD practices, with a focus on observability and integration within distributed systems.

Highest-signal resume keywords

Kubernetes Infrastructure DesignGo Programming SkillsGPU Workload ManagementCI/CD and Infrastructure-as-CodeHelm Chart Development

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Applicant Tracking System Keywords

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Hard Skills

KubernetesGoCI/CDInfrastructure-as-CodeHelmGPU WorkloadsLLM InferenceObservabilityModel Lifecycle ManagementAPI Integration

Soft Skills

AutonomyCollaborationWritten Communication

Tools & Technologies

Claude CodeOpenAI Codex

Industry Keywords

Distributed SystemsEnterprise DeploymentAir-Gapped InstallsSSO/OIDCSupply-Chain SecurityQuantizationBatchingCachingUI DevelopmentOpen-Source Contributions

Tech Stack

Tools & technologies

Distributed SystemsKubernetesReactTypeScriptGo

About the role

Key responsibilities & impact

Design and build LLM serving infrastructure on Kubernetes
Implement deployment, GPU scheduling, scaling, and model lifecycle management
Package the platform for enterprise environments using Helm-based installs and upgrades
Support deployments in restricted and offline networks
Integrate the serving layer with API gateway, identity, and metering services
Build observability for production GPU inference, including serving metrics and GPU telemetry
Contribute across a multi-service codebase
Help set engineering direction through design documents and code reviews

Requirements

What you’ll need

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 working with high autonomy on a small, remote-first, written-culture team
Nice to have: inference performance work, including 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

Comp & perks

Professional development and training
Conference and working group attendance
Company outings, happy hours, hackathons, and tech talks
Competitive compensation package with a strong benefits plan
Opportunity to work with passionate colleagues and Fortune 500 and Global 2000 customers
Open-source innovation environment
Continuous growth environment