Senior Software Engineer, AI Infrastructure

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.

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.