[Hiring] Platform Engineer @Vectara

Role Description

You'll own the infrastructure that runs our deploy anywhere platform — from Kubernetes clusters serving ML inference at scale to the CI/CD pipelines, IaC, and observability stack that keep it all reliable. This is a hands-on role: you'll write Helm charts and Terraform one day, debug a Kafka consumer lag issue the next, and ship a backend service feature the day after. You'll deploy across AWS, GCP, and on-premises (including air-gapped environments), and you'll participate in an on-call rotation supporting enterprise customers.

What You’ll Do

• Build and maintain infrastructure-as-code (Terraform, Helm) for our AWS EKS and GCP GKE clusters, plus on-premises deployments (including Tanzu and air-gapped environments).
• Own CI/CD pipelines (GitHub Actions, Bazel, ArgoCD) and drive GitOps adoption.
• Deploy, scale, and optimize ML/NLP inference workloads (vLLM, PyTorch, GPU scheduling with various Kubernetes scalers).
• Build and improve observability: Prometheus, Grafana, Datadog, and OpenTelemetry.
• Collaborate with Field Engineering to support PoCs and platform deployments in customer cloud VPCs and on-prem environments.
• Contribute to backend services (Java 21, Python, gRPC) and platform features.
• Improve system reliability, scalability, and developer experience across the engineering org.

Qualifications

• 2+ years in platform engineering, DevOps, SRE, or backend infrastructure roles.
• Strong Kubernetes experience (deployment, debugging, scaling — not just `kubectl apply`).
• 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).
• Proficiency in one or more of: Go, Python, Java. Comfortable reading and contributing to backend codebases.
• Working knowledge of CI/CD systems (GitHub Actions, Bazel, ArgoCD, or similar).
• Solid fundamentals in Linux, networking, and distributed systems.

Requirements

• 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.
• 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.

Benefits

• Every full-time team member is also an equity owner, offering the potential for significant long-term financial gain.
• Commitment to ensuring employees are true economic partners in the company's success.

Company Description

Vectara's RAG and Agentic AI platform helps enterprises deploy AI agents and assistants that are accurate, secure, and explainable. We built the Hughes Hallucination Evaluation Model (HHEM) — #1 on HuggingFace with 5.5M+ downloads, cited in the New York Times and Visual Capitalist — and Mockingbird, a purpose-built LLM optimized for retrieval-augmented generation. Over 100 enterprise customers across high tech, defense, financial services, healthcare, and manufacturing trust our platform in production.

We're a ~50-person team backed by ~$70M in funding, founded by neural information retrieval and distributed systems experts from Google. Alumni of Cloudera, Splunk, MongoDB, and Elastic round out a team building the infrastructure layer for trustworthy enterprise AI.