webAI
Staff Platform / Infrastructure Engineer
Austin, TX · Staff+
Sponsorship not specifiedDetected 1 day ago
PythonGoRustBashNode.jsGitAWSAzureDockerKubernetesTerraformAnsibleCI/CDLinuxPrometheusGrafanaLLMsIncident ResponseSupply ChainIntellectual PropertyEmbedded SystemsLoad TestingDNSFirewall
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odds of building a lasting career here
37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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Files H-1B transfers
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About the role
- That means how our kernel, services and local model inference get packaged, deployed, secured, observed and upgraded across bare metal and cloud.
- This is a hands-on staff role: you'll make the architecture calls, write the code and carry the pager.
- Cut custom infrastructure code where you can.
Responsibilities
- Own deployment for the webAI kernel and B2B SDK. Deliver single-machine installs, multi-node clusters, and cloud (AWS, Azure/AKS) installs from one model, keeping the gap between cloud and bare metal small.
- Build the inference serving layer with the AI team: an OpenAI-compatible model gateway, conversation-pinned load balancing, routing per model and per persona, and performance/load testing (throughput, time to first token, concurrency).
- Own the software supply chain: GitLab CI, container and OCI model artifacts, signing (cosign/minisign), pinned dependencies, mirrored registries for air-gapped sites, and the release process.
- Define what high availability means for us. Set reliability levels and SLOs we can commit to in customer contracts, then build them.
- 8+ years building and operating production infrastructure. At least some of it on bare metal or on-prem, not only managed cloud.
Nice to have
- macOS fleet administration at scale (launchd, pf, MDM-managed or locked-down environments, FileVault constraints).
- Running local LLM inference (llama.cpp, MLX, vLLM), GPU/unified-memory capacity planning, model packaging.
- Air-gapped or disconnected delivery: mirrored registries, offline installers.
- Peer-to-peer or QUIC networking (e.g. iroh, libp2p), relays and NAT traversal.
- Writing Kubernetes operators/controllers or Nomad tooling (kube-rs, controller-runtime).
- Customer-facing deployment experience: installing and supporting software at customer sites.
- We seek individuals who exemplify the following:
- Truth - Emphasizing transparency and honesty in every interaction and decision.
Skills
- Deep experience with at least one workload orchestrator (Nomad or Kubernetes), and the judgment to know when not to use one.
- Strong Terraform and configuration management (Ansible or similar). Clean state and environment management across staging and production.
- Production experience with AWS, Azure, or both (identity/IAM, KMS, container registries, managed Kubernetes).
- Secrets and identity: Vault or equivalent, PKI/mTLS, OIDC.
- Observability: Prometheus/Grafana/Loki or equivalent, alert design, running on-call.
- Proficiency in at least one systems language (Rust or Go), plus scripting (Python/Bash).
Compensation
- Competitive salary and performance-based incentives
Benefits
- We strive to provide competitive benefits to all employees.
- The benefits listed in this posting generally apply to U.S.-based employees.
- For employees hired outside the United States, benefits may vary based on local law, country-specific requirements, and the employment platform or entity through which the employee is hired.
- Comprehensive health, dental, and vision benefits package
- Including a high-deductible HSA option with company contribution
- Flexible PTO Policy
- Parental leave for eligible employees
- Continuing education support
- Basic, company-paid life insurance
- Supplemental life insurance
- Company-paid short and long term disability
- We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline.
Company info
- webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI.
- We recognize the evolving demands of a data-driven society for scalability and flexibility, and we firmly believe that the future of AI lies in distributed processing at the edge, bringing computation closer to the source of data generation.
- We are developing an end-to-end platform that is secure, scalable, and fully under the control of our users, empowering enterprises with AI that understands their unique business.
- We are a team driven by truth, ownership, tenacity, and humility, and we seek individuals who resonate with these core values and are passionate about shaping the next generation of AI.
- Our mission is to build a future where a company's valuable data and intellectual property remain entirely private, enabling the deployment of large-scale AI models directly on standard consumer hardware without compromising the information embedded within those models.
- Write the runbooks, "recipes" and RCAs that let forward-deployed engineers and customers operate the stack without you. Lead incident response when they can't.
This listing is sourced directly from webAI's careers page and normalized into a canonical job model.