jobapplier

Platform Engineer

Vectara

Skills

Required

  • Terraform / Helm / Pulumi
  • CI/CD
  • Kubernetes
  • infrastructure-as-code
  • cloud provider
  • AWS
  • GCP / Azure
  • Linux
  • Bazel
  • Go
  • Python
  • Java
  • Kafka
  • Pulsar
  • MariaDB / PostgreSQL

Preferred

  • infrastructure
  • observability tooling
  • Prometheus
  • Grafana
  • OpenTelemetry
  • Datadog
  • AI-assisted
  • development workflows

Join our team as a Platform Engineer, where you'll be responsible for owning the infrastructure that runs our deploy anywhere platform.

Responsibilities

  • This hands-on role involves writing Helm charts and Terraform, debugging issues, and shipping backend service features.
  • You'll deploy across multiple cloud providers and on-premises environments, and participate in an on-call rotation supporting enterprise customers.
  • Additionally, you'll build and maintain infrastructure-as-code, own CI/CD pipelines, deploy and optimize ML/NLP inference workloads, improve observability, collaborate with Field Engineering, contribute to backend services, and enhance system reliability and scalability.
  • Posséder l'infrastructure qui fait fonctionner notre plateforme de déploiement partout, y compris les clusters Kubernetes et les pipelines CI/CD.
  • Écrire des charts Helm et du code Terraform, déboguer des problèmes et expédier des fonctionnalités de service backend.
  • Déployer sur AWS, GCP et sur site, et participer à une rotation d'astreinte pour soutenir les clients d'entreprise.

Requirements

  • Solid fundamentals in Linux, networking, and distributed systems

Hands-on with infrastructure-as-code: Terraform, Helm, or Pulumi

  • Experience with at least one major cloud provider (AWS preferred; GCP or Azure also valued)
  • Working knowledge of CI/CD systems (GitHub Actions, Bazel, ArgoCD, or similar)
  • Proficiency in one or more of: Go, Python, Java. Comfortable reading and contributing to backend codebases
  • Strong Kubernetes experience (deployment, debugging, scaling — not just `kubectl apply`)
  • 2+ years in platform engineering, DevOps, SRE, or backend infrastructure roles
  • Experience deploying or operating ML inference workloads (model serving, GPU scheduling, vLLM, TensorFlow Serving, or similar)
  • Familiarity with streaming/messaging systems (Kafka, Pulsar) and data stores (MariaDB/PostgreSQL, Aerospike, ClickHouse, OpenSearch)
  • Experience with GitOps workflows (ArgoCD, Flux)
  • Exposure to air-gapped or on-premises Kubernetes deployments

Preferred

  • Background in observability tooling (Prometheus, Grafana, OpenTelemetry, Datadog)
  • Experience providing technical support or working directly with enterprise customers on infrastructure issues
  • Comfort with AI-assisted development workflows and managing AI coding agents