Job description

Platform Engineer Vectara is the Enterprise Agent Platform that enables businesses to build and deploy governed, grounded, auditable AI agents across SaaS, VPC, and on-prem. We have developed our own models, observability and orchestration layers, guardrails, and context management systems in order to provide our customers with the greatest levels of AI agent accuracy, security, and explainability. Our founding members include industry veterans and experts in neural information retrieval and distributed systems from Google. We’re a passionate team that’s hyper-focused on solving enterprise-level technology and business problems with AI. Join us! The Role 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. What You’ll Bring (Required): 5+ 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. What Sets You Apart (Preferred) 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. Location requirements: We support remote applicants from all over the US but candidates who can come to the office 2-3 days a week in our Palo Alto office are preferred. Perks and Benefits: 100% paid Medical, Dental, Vision for employees. Option of Health Savings Account (HSA) or Flexible Savings Account (FSA). Generous paid time off (PTO) plus paid sick time and holidays. Professional development and training opportunities. Company virtual happy hours and fun team building activities and more. Salary is just one component of Vectara’s employee compensation. Our full-time employees are also equity owners in the company, which although not an immediate cash component, can have positive impacts on long-term total compensation for each participating employee. We would be remiss if we didn’t highlight and celebrate our focus on engaging many of our employees in being economic co-owners of the business. Vectara welcomes all. We value the collective wisdom of people from different backgrounds, experiences, abilities and perspectives. We never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. Vectara has a positive and supportive culture—we look for people who are inventive and work to be a little better every single day. We seek to be smart, humble, hardworking and, above all, curious. After all, we are on a mission to find meaning.

Requirements

Must-haves

Platform Engineer
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.
5+ 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.
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.
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.

Nice-to-haves

Experience with at least one major cloud provider (AWS preferred; GCP or Azure also valued).
What Sets You Apart (Preferred)
We support remote applicants from all over the US but candidates who can come to the office 2-3 days a week in our Palo Alto office are preferred.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aikubernetesmlci/cdawsgcpjavapythonazurego

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Paid Time Off

Professional Development